WWW2018.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# Entity Stats Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "hidden": true
   },
   "outputs": [],
   "source": [
    "from pymongo import MongoClient\n",
    "import nltk\n",
    "import config as cfg\n",
    "import pandas as pd\n",
    "sent_detector = nltk.data.load('tokenizers/punkt/english.pickle')\n",
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "hidden": true
   },
   "outputs": [],
   "source": [
    "client = MongoClient('localhost:' + str(cfg.mongoDB_Port))\n",
    "\n",
    "db = client.pub\n",
    "pub = client.pub.publications\n",
    "ent = client.pub.entities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "hidden": true
   },
   "outputs": [],
   "source": [
    "mongo_string_search = {'$and': [{'label': 'dataset'}, {'paper_id': {'$exists': True}}]}                \n",
    "results = db.entities.find(mongo_string_search)\n",
    "datasets = []\n",
    "for i, r in enumerate(results):\n",
    "    datasets.append(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true,
    "hidden": true
   },
   "outputs": [],
   "source": [
    "mongo_string_search = {'$and': [{'label': 'method'}, {'paper_id': {'$exists': True}}]}                \n",
    "results = db.entities.find(mongo_string_search)\n",
    "methods = []\n",
    "for i, r in enumerate(results):\n",
    "    methods.append(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true,
    "hidden": true
   },
   "outputs": [],
   "source": [
    "ds_names = []\n",
    "for ds in datasets:\n",
    "    ds_names.append(ds['filtered_words'])\n",
    "ds_count = Counter(ds_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('TREC', 1792),\n",
       " ('VLDB', 1336),\n",
       " ('Microsoft', 676),\n",
       " ('PageRank', 486),\n",
       " ('SIGIR', 443),\n",
       " ('BM25', 384),\n",
       " ('Intel', 332),\n",
       " ('Lucene', 331),\n",
       " ('WordNet', 327),\n",
       " ('Wikipedia', 310),\n",
       " ('Jaccard', 297),\n",
       " ('Google', 287),\n",
       " ('XML', 278),\n",
       " ('SPARQL', 275),\n",
       " ('XPath', 265)]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_count.most_common(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true,
    "hidden": true
   },
   "outputs": [],
   "source": [
    "ds_names = []\n",
    "for ds in datasets:\n",
    "    if ds['dssimilarity'] > ds['mtsimilarity']:\n",
    "        ds_names.append(ds['filtered_words'])\n",
    "ds_count = Counter(ds_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": false,
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('TREC', 1792),\n",
       " ('VLDB', 1336),\n",
       " ('Microsoft', 676),\n",
       " ('SIGIR', 443),\n",
       " ('Intel', 332),\n",
       " ('Lucene', 331),\n",
       " ('WordNet', 327),\n",
       " ('Wikipedia', 310),\n",
       " ('Google', 287),\n",
       " ('XML', 278),\n",
       " ('SPARQL', 275),\n",
       " ('RDBMS', 252),\n",
       " ('JavaScript', 241),\n",
       " ('URIs', 206),\n",
       " ('DBLP', 201),\n",
       " ('OLAP', 192),\n",
       " ('Twitter', 189),\n",
       " ('WHERE', 171),\n",
       " ('DEMONSTRATION', 158),\n",
       " ('DBpedia', 147),\n",
       " ('NIST', 144),\n",
       " ('XSLT', 138),\n",
       " ('PostgreSQL', 132),\n",
       " ('OLTP', 130),\n",
       " ('ASCII', 129),\n",
       " ('Hadoop', 126),\n",
       " ('IEEE', 122),\n",
       " ('PubMed', 118),\n",
       " ('SMART', 115),\n",
       " ('DBMSs', 114)]"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_count.most_common(30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true,
    "hidden": true
   },
   "outputs": [],
   "source": [
    "mt_names = []\n",
    "for mt in methods:\n",
    "    mt_names.append(mt['filtered_words'])\n",
    "mt_count = Counter(mt_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "hidden": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('TREC', 1917),\n",
       " ('HTML', 875),\n",
       " ('VLDB', 795),\n",
       " ('URLs', 499),\n",
       " ('International Wide World', 463),\n",
       " ('DBMS', 430),\n",
       " ('HTTP', 384),\n",
       " ('Web', 340),\n",
       " ('National Foundation Science', 331),\n",
       " ('Java', 306),\n",
       " ('Information  Retrieval', 298),\n",
       " ('INTRODUCTION', 284),\n",
       " ('Wikipedia', 277),\n",
       " ('NIST', 276),\n",
       " ('SPARQL', 267)]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt_count.most_common(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true,
    "hidden": true
   },
   "outputs": [],
   "source": [
    "mt_names = []\n",
    "for mt in methods:\n",
    "    if mt['mtsimilarity'] > mt['dssimilarity']:\n",
    "        mt_names.append(mt['filtered_words'])\n",
    "mt_count = Counter(mt_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": false,
    "hidden": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('DBMS', 430),\n",
       " ('Information  Retrieval', 298),\n",
       " ('INTRODUCTION', 284),\n",
       " ('Boolean', 223),\n",
       " ('PageRank', 202),\n",
       " ('learning', 159),\n",
       " ('NDCG', 157),\n",
       " ('MapReduce', 149),\n",
       " ('Jaccard', 145),\n",
       " ('Gaussian', 136),\n",
       " ('Information Retrieval', 115),\n",
       " ('retrieval information', 113),\n",
       " ('XPath', 113),\n",
       " ('Vector Machines Support', 112),\n",
       " ('Dirichlet', 109),\n",
       " ('Vector Machine Support', 109),\n",
       " ('Bayesian', 101),\n",
       " ('XQuery', 97),\n",
       " ('Okapi', 84),\n",
       " ('Information Intelligent Retrieval', 83),\n",
       " ('Vector Model Space', 82),\n",
       " ('Cartesian', 77),\n",
       " (' retrieval information', 76),\n",
       " ('CPUs', 75),\n",
       " ('Markov', 74),\n",
       " ('machine vector support', 73),\n",
       " ('NULL', 72),\n",
       " ('machines vector support', 71),\n",
       " ('function likelihood', 65),\n",
       " ('Euclidean', 64),\n",
       " ('HARD', 55),\n",
       " ('SVMs', 54),\n",
       " ('retrieval  information', 53),\n",
       " ('Advancement', 51),\n",
       " ('Poisson', 51),\n",
       " ('RMSE', 50),\n",
       " ('FIFO', 50),\n",
       " ('PRELIMINARIES', 49),\n",
       " ('Pearson', 49),\n",
       " ('Algorithm', 49),\n",
       " ('retrieval In information', 48),\n",
       " ('Laplacian', 45),\n",
       " ('ANOVA', 45),\n",
       " ('MBRs', 44),\n",
       " ('COTS', 43),\n",
       " ('Viterbi', 43),\n",
       " ('ANALYSIS', 41),\n",
       " ('Lagrange', 39),\n",
       " ('Indexing Latent Semantic', 37),\n",
       " ('SIFT', 36)]"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt_count.most_common(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ElasticSearch "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from elasticsearch import Elasticsearch\n",
    "from elasticsearch import helpers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "es = Elasticsearch(\n",
    "    [{'host': 'localhost', 'port': 9200}], timeout=30, max_retries=10, retry_on_timeout=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 598,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# es.cluster.health()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got 32 Hits:\n",
      "conf_icra_SunF16 NEOL: Toward Never-Ending Object Learning for robots.\n",
      "ICRA\n",
      "conf_icra_GoehringHRSD14 Interactive adaptation of real-time object detectors.\n",
      "ICRA\n",
      "journals_ml_MesnilBWCB14 Learning semantic representations of objects and their parts.\n",
      "Machine Learning\n",
      "conf_icdm_ZhuangLJXLH15 Representation Learning via Semi-Supervised Autoencoder for Multi-task Learning.\n",
      "ICDM\n",
      "journals_ml_WestonBU10 Large scale image annotation: learning to rank with joint word-image embeddings.\n",
      "Machine Learning\n"
     ]
    }
   ],
   "source": [
    "res = es.search(index = \"ir_full\", body = {\"query\": {\"match\": {\"content\" : \"imagenet\"}}}, size = 5)\n",
    "\n",
    "print(\"Got %d Hits:\" % res['hits']['total'])\n",
    "for hit in res['hits']['hits']:\n",
    "    print(hit['_id'], hit['_source']['title'])\n",
    "    print(hit['_source']['journal'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got 96939 Hits:\n"
     ]
    }
   ],
   "source": [
    "res = es.search(index = \"ir\", body = {}, size = 5)\n",
    "\n",
    "print(\"Got %d Hits:\" % res['hits']['total'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 513,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got 4 Hits:\n",
      "conf_trec_MiyanishiOLSU11 15.950895 TREC 2011 Microblog Track Experiments at Kobe University.\n",
      "\n",
      "conf_icwsm_HuTK13 14.513167 Dude, srsly?: The Surprisingly Formal Nature of Twitter's Language.\n",
      "\n",
      "conf_sigir_ChaC12 13.6760025 Social-network analysis using topic models.\n",
      "\n",
      "conf_sigir_ChaBHC13 13.222706 Incorporating popularity in topic models for social network analysis.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "res = es.search(index = \"ir\", body = \n",
    "                {\n",
    "                    \"query\" : {\n",
    "                        \"bool\": {\n",
    "                            \"must\": [{\"match_phrase\" : {\"text\" : 'latent semantic indexing'}},\n",
    "                                    {\"match_phrase\" : {\"text\" : 'twitter'}}]\n",
    "                        }\n",
    "                    }\n",
    "                }, size = 5)\n",
    "\n",
    "\n",
    "print(\"Got %d Hits:\" % res['hits']['total'])\n",
    "for hit in res['hits']['hits']:\n",
    "    print(hit['_id'], hit['_score'], hit['_source']['title'])\n",
    "#     print(hit['_source']['text'])\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 628,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "query = 'image classification, imagenet' \n",
    "query = 'support vector machine, trec' \n",
    "query = 'latent semantic indexing, twitter'\n",
    "# query = 'crispr cancer gene'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 632,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "queries = ['image classification, imagenet', 'support vector machine, trec', \n",
    "           'latent semantic indexing, twitter', 'word embedding, wikipedia']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 636,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['image classification', 'imagenet']\n",
      "Got 1 Hits:\n",
      "conf_sigir_PanYMLNR14 10.419529 Click-through-based cross-view learning for image search.\n",
      "\n",
      "image classification imagenet\n",
      "Got 5048 Hits:\n",
      "conf_sigir_PanYMLNR14 13.019814 Click-through-based cross-view learning for image search.\n",
      "conf_www_FuMYLR15 12.191383 Tagging Personal Photos with Transfer Deep Learning.\n",
      "conf_www_MaekawaHN06 8.419228 Image classification for mobile web browsing.\n",
      "conf_sigir_SrikanthVBM05 8.315823 Exploiting ontologies for automatic image annotation.\n",
      "conf_sigir_DrewL01 8.30496 Construction of a Hierarchical Classifier Schema Using a Combination of Text-Based and Image-Based Approaches.\n",
      "__________________________________________________\n",
      "\n",
      "['support vector machine', 'trec']\n",
      "Got 45 Hits:\n",
      "conf_trec_SiK05 12.870042 Thresholding Strategies for Text Classifiers: TREC 2005 Biomedical Triage Task Experiments.\n",
      "conf_trec_LeeKA02 12.056616 TREC 11 Experiments at NII: The Effects of Virtual Relevant Documents in Batch Filtering.\n",
      "conf_trec_KjerstenM12 11.141617 The HLTCOE Approach to the TREC 2012 KBA Track.\n",
      "conf_trec_LiZHHZ05 11.070509 Learning Domain-Specific Knowledge from Context--THUIR at TREC 2005 Genomics Track.\n",
      "conf_sigir_SantosMO11 11.034777 Intent-aware search result diversification.\n",
      "\n",
      "support vector machine trec\n",
      "Got 12499 Hits:\n",
      "conf_trec_LeeKA02 13.285715 TREC 11 Experiments at NII: The Effects of Virtual Relevant Documents in Batch Filtering.\n",
      "conf_trec_SiK05 12.998962 Thresholding Strategies for Text Classifiers: TREC 2005 Biomedical Triage Task Experiments.\n",
      "conf_trec_KazawaHIM02 12.280322 A Machine Learning Approach for QA and Novelty Tracks: NTT System Description.\n",
      "conf_sigir_ZhangL03 12.204733 Question classification using support vector machines.\n",
      "conf_trec_LiZHHZ05 11.776018 Learning Domain-Specific Knowledge from Context--THUIR at TREC 2005 Genomics Track.\n",
      "__________________________________________________\n",
      "\n",
      "['latent semantic indexing', 'twitter']\n",
      "Got 4 Hits:\n",
      "conf_trec_MiyanishiOLSU11 15.950895 TREC 2011 Microblog Track Experiments at Kobe University.\n",
      "conf_icwsm_HuTK13 14.513167 Dude, srsly?: The Surprisingly Formal Nature of Twitter's Language.\n",
      "conf_sigir_ChaC12 13.6760025 Social-network analysis using topic models.\n",
      "conf_sigir_ChaBHC13 13.222706 Incorporating popularity in topic models for social network analysis.\n",
      "\n",
      "latent semantic indexing twitter\n",
      "Got 5115 Hits:\n",
      "conf_trec_MiyanishiOLSU11 18.708591 TREC 2011 Microblog Track Experiments at Kobe University.\n",
      "conf_sigir_ChaC12 16.128004 Social-network analysis using topic models.\n",
      "conf_sigir_ChaBHC13 16.004646 Incorporating popularity in topic models for social network analysis.\n",
      "conf_icwsm_RamageDL10 15.414259 Characterizing Microblogs with Topic Models.\n",
      "conf_sigir_Ding99 14.955415 A Similarity-based Probability Model for Latent Semantic Indexing.\n",
      "__________________________________________________\n",
      "\n",
      "['word embedding', 'wikipedia']\n",
      "Got 3 Hits:\n",
      "conf_sigir_FangMOH16a 15.722925 Using Word Embedding to Evaluate the Coherence of Topics from Twitter Data.\n",
      "conf_trec_CanoSG14 13.889469 Distributed Non-Parametric Representations for Vital Filtering: UW at TREC KBA 2014.\n",
      "conf_www_KulkarniAPS15 10.571001 Statistically Significant Detection of Linguistic Change.\n",
      "\n",
      "word embedding wikipedia\n",
      "Got 3981 Hits:\n",
      "conf_sigir_FangMOH16a 15.942562 Using Word Embedding to Evaluate the Coherence of Topics from Twitter Data.\n",
      "conf_trec_CanoSG14 15.54724 Distributed Non-Parametric Representations for Vital Filtering: UW at TREC KBA 2014.\n",
      "conf_sigir_ZwicklbauerSG16 15.436344 Robust and Collective Entity Disambiguation through Semantic Embeddings.\n",
      "conf_www_KulkarniAPS15 15.3431425 Statistically Significant Detection of Linguistic Change.\n",
      "conf_sigir_JGV16 15.302531 Doc2Sent2Vec: A Novel Two-Phase Approach for Learning Document Representation.\n",
      "__________________________________________________\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for query in queries:\n",
    "    terms = [x.strip() for x in query.split(',')]\n",
    "    if len(terms) == 2:\n",
    "        doc = { \"query\" : { \"bool\": { \"must\": [{\"match_phrase\" : {\"text\" : terms[0]}},\n",
    "                                               {\"match_phrase\" : {\"text\" : terms[1]}}]}}}\n",
    "\n",
    "        doc = json.dumps(doc)\n",
    "        print(terms)\n",
    "        res = es.search(index = \"ir\", body = doc, size = 5)\n",
    "        print(\"Got %d Hits:\" % res['hits']['total'])\n",
    "        for hit in res['hits']['hits']:\n",
    "            print(hit['_id'], hit['_score'], hit['_source']['title'])\n",
    "    #         print(hit['_source']['text'])\n",
    "    #         print('')\n",
    "\n",
    "    print('')\n",
    "\n",
    "    terms = query.replace(',', '')\n",
    "    doc = { \"query\" : { \"bool\": { \"must\": [{\"match\" : {\"text\" : terms}}]}}}\n",
    "    doc = json.dumps(doc)\n",
    "    res = es.search(index = \"ir\", body = doc, size = 5)\n",
    "    print(terms)\n",
    "    print(\"Got %d Hits:\" % res['hits']['total'])\n",
    "    for hit in res['hits']['hits']:\n",
    "        print(hit['_id'], hit['_score'], hit['_source']['title'])\n",
    "    #         print(hit['_source']['text'])\n",
    "    #     print('')\n",
    "    print('_'*50)\n",
    "    print('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got 5 Hits:\n",
      "conf_trec_MiyanishiOLSU11 18.708591 TREC 2011 Microblog Track Experiments at Kobe University.\n",
      "conf_sigir_ChaC12 16.128004 Social-network analysis using topic models.\n",
      "conf_sigir_ChaBHC13 16.004646 Incorporating popularity in topic models for social network analysis.\n",
      "conf_icwsm_HuTK13 14.513167 Dude, srsly?: The Surprisingly Formal Nature of Twitter's Language.\n",
      "conf_jcdl_SalahEldeenN15 14.172043 Predicting Temporal Intention in Resource Sharing.\n"
     ]
    }
   ],
   "source": [
    "res = es.search(index = \"ir\", body = {\"query\": {\"common\": { \n",
    "    \"text\": {\"query\": query, \"cutoff_frequency\": 0.01}}}}, \n",
    "    size = 5)\n",
    "\n",
    "print(\"Got %d Hits:\" % res['hits']['total'])\n",
    "for hit in res['hits']['hits']:\n",
    "    print(hit['_id'], hit['_score'], hit['_source']['title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got 5158 Hits:\n",
      "conf_sigir_WangXLC11 62.174545 Regularized latent semantic indexing.\n",
      "conf_sigir_Hofmann99 60.32915 Probabilistic Latent Semantic Indexing.\n",
      "conf_sigir_Efron07 56.72454 Model-averaged latent semantic indexing.\n",
      "conf_sigir_YuYT05 54.89106 Multi-label informed latent semantic indexing.\n",
      "conf_trec_GarronK11 51.606586 Latent Semantic Indexing with selective Query Expansion.\n"
     ]
    }
   ],
   "source": [
    "res = es.search(index = \"ir\", body = {\"query\": { \"multi_match\" : {\n",
    "    \"query\" : query, \"fields\" : [ \"title^3\", \"abstract^2\", \"text\"], \n",
    "    \"type\" : \"best_fields\", \"tie_breaker\": 0.2}}}, size = 5)\n",
    "\n",
    "print(\"Got %d Hits:\" % res['hits']['total'])\n",
    "for hit in res['hits']['hits']:\n",
    "    print(hit['_id'], hit['_score'], hit['_source']['title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got 5158 Hits:\n",
      "conf_sigir_WangXLC11 73.06489 Regularized latent semantic indexing.\n",
      "conf_sigir_Hofmann99 72.1853 Probabilistic Latent Semantic Indexing.\n",
      "conf_sigir_YuYT05 66.35928 Multi-label informed latent semantic indexing.\n",
      "conf_sigir_Efron07 66.26198 Model-averaged latent semantic indexing.\n",
      "conf_sigir_Ding99 61.74302 A Similarity-based Probability Model for Latent Semantic Indexing.\n"
     ]
    }
   ],
   "source": [
    "res = es.search(index = \"ir\", body = {\"query\": { \"multi_match\" : {\n",
    "    \"query\" : query, \"fields\" : [ \"title^3\", \"abstract^2\", \"text\"],\n",
    "    \"type\" : \"most_fields\"}}}, size = 5)\n",
    "\n",
    "print(\"Got %d Hits:\" % res['hits']['total'])\n",
    "for hit in res['hits']['hits']:\n",
    "    print(hit['_id'], hit['_score'], hit['_source']['title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got 314 Hits:\n",
      "conf_sigir_WangXLC11 19.817318 Regularized latent semantic indexing.\n",
      "conf_sigir_Hofmann99 19.121704 Probabilistic Latent Semantic Indexing.\n",
      "conf_trec_MiyanishiOLSU11 18.708591 TREC 2011 Microblog Track Experiments at Kobe University.\n",
      "conf_sigir_Efron07 18.113392 Model-averaged latent semantic indexing.\n",
      "conf_sigir_YuYT05 17.341335 Multi-label informed latent semantic indexing.\n"
     ]
    }
   ],
   "source": [
    "res = es.search(index = \"ir\", body = {\"query\": { \"multi_match\" : {\n",
    "    \"query\" : query, \"fields\" : [ \"title\", \"abstract\", \"text\"], \n",
    "    \"type\" : \"most_fields\", \"cutoff_frequency\": 0.01}}}, size = 5)\n",
    "\n",
    "print(\"Got %d Hits:\" % res['hits']['total'])\n",
    "for hit in res['hits']['hits']:\n",
    "    print(hit['_id'], hit['_score'], hit['_source']['title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got 5 Hits:\n",
      "conf_trec_MiyanishiOLSU11 18.708591 TREC 2011 Microblog Track Experiments at Kobe University.\n",
      "conf_sigir_ChaC12 16.128004 Social-network analysis using topic models.\n",
      "conf_sigir_ChaBHC13 16.004646 Incorporating popularity in topic models for social network analysis.\n",
      "conf_icwsm_HuTK13 14.513167 Dude, srsly?: The Surprisingly Formal Nature of Twitter's Language.\n",
      "conf_jcdl_SalahEldeenN15 14.172043 Predicting Temporal Intention in Resource Sharing.\n"
     ]
    }
   ],
   "source": [
    "res = es.search(index = \"ir\", body = {\"query\": {\"query_string\" : {\n",
    "    \"default_field\" : \"text\", \"default_operator\" : \"AND\",\n",
    "    \"query\" : \"('latent semantic indexing') AND (twitter)\"}}}, size = 5)\n",
    "\n",
    "print(\"Got %d Hits:\" % res['hits']['total'])\n",
    "for hit in res['hits']['hits']:\n",
    "    print(hit['_id'], hit['_score'], hit['_source']['title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# Lemmatize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package wordnet to /home/ubuntu/nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n"
     ]
    }
   ],
   "source": [
    "import nltk\n",
    "from pymongo import MongoClient\n",
    "from config import mongoDB_Port\n",
    "from nltk.stem import WordNetLemmatizer, SnowballStemmer, LancasterStemmer\n",
    "import string\n",
    "from collections import Counter\n",
    "\n",
    "nltk.download('wordnet')\n",
    "wordnet_lemmatizer = WordNetLemmatizer()\n",
    "lancaster_stemmer = LancasterStemmer()\n",
    "snowball_stemmer = SnowballStemmer(\"english\")\n",
    "tr = str.maketrans(\"\", \"\", string.punctuation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1086,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000\n",
      "20000\n",
      "30000\n",
      "40000\n",
      "50000\n",
      "60000\n",
      "70000\n",
      "80000\n",
      "90000\n",
      "100000\n",
      "110000\n",
      "120000\n",
      "130000\n",
      "140000\n",
      "150000\n",
      "160000\n"
     ]
    }
   ],
   "source": [
    "client = MongoClient('localhost:' + str(mongoDB_Port))\n",
    "db = client.pub\n",
    "pub = client.pub.publications\n",
    "es = Elasticsearch(\n",
    "    [{'host': 'localhost', 'port': 9200}], timeout=30, max_retries=10, retry_on_timeout=True\n",
    ")\n",
    "es.cluster.health(wait_for_status='yellow', request_timeout=1)\n",
    "allentities = db.entities.find()\n",
    "words = []\n",
    "stems = []\n",
    "lemmas = []\n",
    "cleans = []\n",
    "x = 0\n",
    "for rr in allentities:\n",
    "    word = rr['word'].lower()\n",
    "    lemma  = wordnet_lemmatizer.lemmatize(word)\n",
    "    stem = snowball_stemmer.stem(word)\n",
    "    no_punkt = word.translate(tr)\n",
    "    clean = ''.join([i for i in no_punkt if not i.isdigit()])\n",
    "    lower = rr['word'].lower()\n",
    "    \n",
    "    db.entities.update_one({'_id' : rr['_id']}, \n",
    "                           {\"$set\" : {'lemma': lemma, 'stem': stem, \n",
    "                                      'clean': clean, 'no_punkt': no_punkt,\n",
    "                                      'word_lower' : lower}}, upsert = False)\n",
    "    x = x + 1\n",
    "    if x % 10000 == 0:\n",
    "        print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "165051 66864 61077 66864 59933\n"
     ]
    }
   ],
   "source": [
    "print(len(words), len(set(words)), len(set(stems)), len(set(lemmas)), len(set(cleans)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "word_count = Counter(words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 758,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "software\n",
      "software\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "noise\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "software\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "software\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "software\n",
      "method\n",
      "noise\n",
      "other\n",
      "other\n",
      "other\n",
      "software\n",
      "other\n",
      "software\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "software\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "software\n",
      "software\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "software\n",
      "other\n",
      "other\n",
      "method\n",
      "noise\n",
      "other\n",
      "dataset\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "software\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "software\n",
      "other\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "software\n",
      "noise\n",
      "method\n",
      "other\n",
      "other\n",
      "software\n",
      "software\n",
      "other\n",
      "other\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "software\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "software\n",
      "software\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "noise\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "software\n",
      "software\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "dataset\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "software\n",
      "method\n",
      "other\n",
      "software\n",
      "software\n",
      "other\n",
      "noise\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "software\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "software\n",
      "other\n",
      "method\n",
      "software\n",
      "dataset\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "noise\n",
      "other\n",
      "software\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "software\n",
      "method\n",
      "software\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "software\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "noise\n",
      "method\n",
      "other\n",
      "other\n",
      "software\n",
      "method\n",
      "method\n",
      "other\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "software\n",
      "other\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "software\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "noise\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "dataset\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "noise\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "software\n",
      "other\n",
      "other\n",
      "other\n",
      "noise\n",
      "software\n",
      "method\n",
      "other\n",
      "method\n",
      "software\n",
      "noise\n",
      "noise\n",
      "software\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "other\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "software\n",
      "other\n",
      "other\n",
      "dataset\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "noise\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "software\n",
      "software\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "software\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "noise\n",
      "other\n",
      "software\n",
      "software\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "dataset\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "software\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "software\n",
      "software\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "software\n",
      "method\n",
      "noise\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "software\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "software\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "noise\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "software\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "software\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "noise\n",
      "method\n",
      "method\n",
      "noise\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "software\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "noise\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "other\n",
      "method\n",
      "other\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "software\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "dataset\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "dataset\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "software\n",
      "other\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "method\n",
      "method\n",
      "noise\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "dataset\n",
      "dataset\n",
      "other\n",
      "method\n",
      "method\n",
      "method\n",
      "other\n"
     ]
    }
   ],
   "source": [
    "client = MongoClient('localhost:' + str(mongoDB_Port))\n",
    "db = client.pub\n",
    "pub = client.pub.publications\n",
    "\n",
    "allentities = db.entities.find()\n",
    "\n",
    "for rr in allentities:\n",
    "    try:\n",
    "        ann = rr['Annotator']\n",
    "        print(ann)\n",
    "    except:\n",
    "        db.entities.update_one({'_id' : rr['_id']}, {\"$set\" : {'Annotator' : 'undefined'}}, upsert = False)\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1118,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "allentities = db.entities.find({'word_lower': {'$regex' : '.*idf-.*'} , 'Annotator': 'undefined' })\n",
    "# allentities = db.entities.find({'word_lower': 'header'})\n",
    "\n",
    "for rr in allentities:\n",
    "#     db.entities.update_one({'_id' : rr['_id']}, {\"$set\" : {'word' : 'Spoken Document Retrieval'}}, upsert = False)\n",
    "    db.entities.update_one({'_id' : rr['_id']}, {\"$set\" : {'Annotator' : 'method'}}, upsert = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Popular Entities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 984,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "query = 'ClueWeb09'\n",
    "id_list = ['conf_trec_PamarthiZB09', 'conf_sigir_PotthastHSGMTW12', 'conf_trec_SmuckerCC09', 'conf_trec_LiXGGYLC12', 'conf_trec_PrasetyaTAM11', 'conf_trec_SerdyukovV09', 'conf_sigir_LeeC13', 'conf_trec_ZhengFW10', 'conf_trec_AlbakourKNF10']\n",
    "# id_list = ['journals_ml_Gonzalez-CastanoGM04', 'conf_icdm_LuoHGR05', 'conf_icdm_DomeniconiG01', 'journals_ml_FungM05', 'journals_ml_GestelSBVVDMV04', 'conf_sigir_GreevyS04', 'conf_icdm_ChenWD02', 'journals_jmlr_ChenWYZ04', 'conf_icdm_CaiNHD11', 'conf_icarcv_NguyenVHM14', 'conf_icse_BrunE04', 'conf_icarcv_LiuW08', 'conf_ercimdl_BeelGSF10', 'conf_trec_LeeKA02', 'conf_icarcv_WongW04', 'journals_pvldb_GrosseLWFL11', 'conf_icarcv_YangHXL06']\n",
    "id_list = ['conf_sigir_VosoughiVR16', 'conf_icdm_YuanWX16', 'conf_icra_JainSKSS16', 'conf_icdm_LiuSDTFFYWLZ16', 'conf_icra_LubarskyWWBN16', 'conf_trec_Savenkov15', 'conf_sigir_YanSW16', 'conf_sigir_LeeALHL16', 'conf_icra_OtteWSZ16']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 638,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "47"
      ]
     },
     "execution_count": 638,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "terms_in_results = []\n",
    "\n",
    "for paper in id_list:\n",
    "    _query_terms = {\n",
    "        'query': {\n",
    "            'match': {\n",
    "                'paper_id': paper\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "    \n",
    "    _query_terms = es.search(index = \"surfall_entities\", doc_type = \"entities\", body = _query_terms)\n",
    "    for doc in _query_terms['hits']['hits']:\n",
    "        terms_in_results.append(doc['_source']['clean'])\n",
    "\n",
    "terms_in_results = list(set(terms_in_results))\n",
    "len(terms_in_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 639,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "import operator\n",
    "\n",
    "entity_occurrences = {}\n",
    "\n",
    "for entity in terms_in_results:\n",
    "    _query_occurrences = {\n",
    "        'query': {\n",
    "            'match_phrase': {\n",
    "                'content': entity\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "    \n",
    "    _query_occurrences = es.search(index = \"surfall\", doc_type = \"pubs\", body = _query_occurrences)\n",
    "    entity_occurrences[entity] = _query_occurrences['hits']['total']\n",
    "\n",
    "sorted_occurences = sorted(entity_occurrences.items(), key=operator.itemgetter(1), reverse=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Upcoming Entities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 640,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "47"
      ]
     },
     "execution_count": 640,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "terms_in_results = []\n",
    "\n",
    "for paper in id_list:\n",
    "    _query_terms = {\n",
    "        'query': {\n",
    "            'match': {\n",
    "                'paper_id': paper\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "    \n",
    "    _query_terms = es.search(index = \"surfall_entities\", doc_type = \"entities\", body = _query_terms)\n",
    "    for doc in _query_terms['hits']['hits']:\n",
    "        terms_in_results.append(doc['_source']['clean'])\n",
    "\n",
    "terms_in_results = list(set(terms_in_results))\n",
    "len(terms_in_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 805,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def popular_upcoming_entities(paper_id_list):\n",
    "    terms_in_results = []\n",
    "\n",
    "    for paper in paper_id_list:\n",
    "        _query_terms = {\n",
    "            'query': {\n",
    "                'match': {\n",
    "                    'paper_id': paper\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "\n",
    "        _query_terms = es.search(index = \"surfall_entities\", doc_type = \"entities\", body = _query_terms)\n",
    "        for doc in _query_terms['hits']['hits']:\n",
    "            terms_in_results.append(doc['_source']['clean'])\n",
    "\n",
    "    terms_in_results = list(set(terms_in_results))\n",
    "    \n",
    "    upcoming = []\n",
    "    entity_occurrences = {}\n",
    "    \n",
    "    for entity in terms_in_results:\n",
    "        _query_occurrences = {\n",
    "            'query': {\n",
    "                'match_phrase': {\n",
    "                    'content': entity\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "\n",
    "        _query_occurrences = es.search(index = \"surfall\", doc_type = \"pubs\", body = _query_occurrences)\n",
    "        years = []\n",
    "        entity_occurrences[entity] = _query_occurrences['hits']['total']\n",
    "        \n",
    "        for doc in _query_occurrences['hits']['hits']:\n",
    "            years.append(doc['_source']['year'])\n",
    "        if years:    \n",
    "            if int(min(years)) > 2010:\n",
    "                upcoming.append(entity)\n",
    "\n",
    "    sorted_occurrences = sorted(entity_occurrences.items(), key=operator.itemgetter(1), reverse=True)\n",
    "    \n",
    "    return upcoming, sorted_occurrences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1037,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def popular_upcoming_entities(paper_id_list):\n",
    "    \n",
    "    terms_in_results = []\n",
    "    terms_labels = {}\n",
    "    entity_occurrences = {}\n",
    "    upcoming_occurrences = {}\n",
    "    \n",
    "    for paper in paper_id_list:\n",
    "        _query_terms = {\n",
    "            \"query\" : {\n",
    "                \"bool\": {\n",
    "                    \"must\": [{\"match\" : {'paper_id': paper}}],\n",
    "                    \"should\": [{\"match\" : {\"annotator\" : 'method'}},\n",
    "                               {\"match\" : {\"annotator\" : 'dataset'}}]\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "\n",
    "        _query_terms = es.search(index = \"surfall_entities\", doc_type = \"entities\", body = _query_terms)\n",
    "        \n",
    "        for hit in _query_terms['hits']['hits']:\n",
    "            entity = hit['_source']['lower']\n",
    "            terms_in_results.append(entity)\n",
    "            terms_labels[entity] = hit\n",
    "\n",
    "    terms_in_results = list(set(terms_in_results))\n",
    "    \n",
    "    for entity in terms_in_results:\n",
    "        _query_occurrences = {\n",
    "            'query': {\n",
    "                'match_phrase': {\n",
    "                    'content': entity\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "\n",
    "        _query_occurrences = es.search(index = \"surfall\", doc_type = \"pubs\", body = _query_occurrences)\n",
    "        years = []\n",
    "        entity_occurrences[entity] = _query_occurrences['hits']['total']\n",
    "        \n",
    "        for doc in _query_occurrences['hits']['hits']:\n",
    "            years.append(doc['_source']['year'])\n",
    "        if years:    \n",
    "            if int(min(years)) > 2010:\n",
    "                upcoming_occurrences[entity] = _query_occurrences['hits']['total']\n",
    "\n",
    "    sorted_occurrences = sorted(entity_occurrences.items(), key=operator.itemgetter(1), reverse=True)\n",
    "    sorted_upcoming = sorted(upcoming_occurrences.items(), key=operator.itemgetter(1), reverse=True)\n",
    "    \n",
    "    triples = []\n",
    "    for pair in sorted_occurrences:\n",
    "        amount = pair[1]\n",
    "        term = pair[0]\n",
    "        \n",
    "        if terms_labels[term]['_source']['annotator'] in ['method', 'dataset']:\n",
    "            actual_label = terms_labels[term]['_source']['annotator']\n",
    "        elif terms_labels[term]['_source']['annotator'] in ['other', 'noise', 'software']:\n",
    "            continue\n",
    "        elif terms_labels[term]['_source']['mt_similarity'] > terms_labels[term]['_source']['ds_similarity']:\n",
    "            actual_label = 'method'\n",
    "        else:\n",
    "            actual_label = 'dataset'\n",
    "        triples.append([term, actual_label, amount])\n",
    "    \n",
    "    return sorted_occurrences, sorted_upcoming, terms_labels, triples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1083,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "query = 'ClueWeb09'\n",
    "id_list = ['conf_trec_PamarthiZB09', 'conf_sigir_PotthastHSGMTW12', 'conf_trec_SmuckerCC09', 'conf_trec_LiXGGYLC12', 'conf_trec_PrasetyaTAM11', 'conf_trec_SerdyukovV09', 'conf_sigir_LeeC13', 'conf_trec_ZhengFW10', 'conf_trec_AlbakourKNF10']\n",
    "# id_list = ['journals_ml_Gonzalez-CastanoGM04', 'conf_icdm_LuoHGR05', 'conf_icdm_DomeniconiG01', 'journals_ml_FungM05', 'journals_ml_GestelSBVVDMV04', 'conf_sigir_GreevyS04', 'conf_icdm_ChenWD02', 'journals_jmlr_ChenWYZ04', 'conf_icdm_CaiNHD11', 'conf_icarcv_NguyenVHM14', 'conf_icse_BrunE04', 'conf_icarcv_LiuW08', 'conf_ercimdl_BeelGSF10', 'conf_trec_LeeKA02', 'conf_icarcv_WongW04', 'journals_pvldb_GrosseLWFL11', 'conf_icarcv_YangHXL06']\n",
    "# id_list = ['conf_sigir_VosoughiVR16', 'conf_icdm_YuanWX16', 'conf_icra_JainSKSS16', 'conf_icdm_LiuSDTFFYWLZ16', 'conf_icra_LubarskyWWBN16', 'conf_trec_Savenkov15', 'conf_sigir_YanSW16', 'conf_sigir_LeeALHL16', 'conf_icra_OtteWSZ16']\n",
    "id_list = ['conf_icdm_LiZWZ11', 'conf_trec_HauptmannYQJCDCBLN02', 'conf_icra_BargotiU16', 'conf_incdm_HijaziCZ10', 'conf_www_MaekawaHN06', 'conf_icdm_ChenCHM13', 'conf_icarcv_LowM10', 'conf_icarcv_MoghadamWM10', 'conf_icdm_KannanTRK11']\n",
    "id_list = ['conf_icwsm_HuttoG14', 'conf_icwsm_VargasMMO16', 'conf_icwsm_AhnGDM10', 'conf_www_HuTGL13', 'conf_esws_SaifFHA14', 'conf_icwsm_MahmudG14', 'conf_icwsm_Dang-XuanS12', 'conf_icwsm_HongS10', 'conf_icwsm_RieisSMPKA15']\n",
    "id_list = ['conf_icra_OzawaC11', 'conf_icra_GarciaD03', 'conf_www_WangK15', 'conf_icra_RamanK14', 'journals_ml_OshersonSW92', 'conf_icra_HareGW15', 'conf_icarcv_Rios-BolivarAM06', 'conf_sigir_YangMXTL16', 'conf_icarcv_WakwellaAK04']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1087,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['sigir', 'dataset', 799],\n",
       " ['enron', 'dataset', 100],\n",
       " ['density function the', 'method', 36],\n",
       " ['nips', 'dataset', 34],\n",
       " ['stage ii ,', 'method', 28],\n",
       " ['cctv', 'dataset', 18],\n",
       " ['detector based on', 'method', 17],\n",
       " ['visual sensors with', 'method', 3],\n",
       " ['events ground truth', 'dataset', 1],\n",
       " ['social information fusion', 'method', 1],\n",
       " ['cmage', 'method', 1],\n",
       " ['concept detection to', 'method', 1]]"
      ]
     },
     "execution_count": 1087,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popular, new, labels, triple_list = popular_upcoming_entities(id_list)\n",
    "triple_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 922,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 922,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[term[0] for term in popular if labels[term[0]] in ['method', 'dataset']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 947,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['chatnoir',\n",
       " 'example entities entity',\n",
       " 'universitas indonesia trec',\n",
       " 'golaxydt2 retrieval models']"
      ]
     },
     "execution_count": 947,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[term[0] for term in new[0:5]]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}