kcem

An Ontology tool kit which is based on kcm and kem

It has 311612 distinct concepts and 1221087 distinct concept-instances

Info of Wiki Dumps

Database changed
mysql> SELECT COUNT(*) FROM categorylinks;
+----------+
| COUNT(*) |
+----------+
| 12490991 |
+----------+
1 row in set (10.10 sec)

mysql> SELECT COUNT(*) FROM page;
+----------+
| COUNT(*) |
+----------+
|  5380929 |
+----------+
1 row in set (5.68 sec)

mysql> 

Install

• (Recommended): Use docker-compose to install

Manually Install

If you want to integrate kcem into your own django project, use manually install.

• pip install kcem

Config

Cause this is a django app

so need to finish these django setups.

1. settings.py：

INSTALLED_APPS = [
    'kcem'
     ...
]

2. urls.py：

import kcem.urls
urlpatterns += [
    url(r'^kcem/', include(kcem.urls))
]

3. python3 manage.py buildkcem --lang <lang, e.g., zh or en or th>
4. fire python manage.py runserver and go 127.0.0.1:8000/ to check whether the config is all ok.

API

1. Get correlated keywords：/kcem

   • keyword

   • num (default=10)

   • example1：http://udiclab.cs.nchu.edu.tw/kcem?keyword=周杰倫&lang=zh

     {
       "origin": "周杰倫",
       "similarity": 1,
       "value": [
         [
           "臺灣男歌手",
           0.1077329254516259
         ],
         [
           "臺灣創作歌手",
           0.08618136696067945
         ],
         [
           "臺灣作詞家",
           0.08453908870383998
         ],
         [
           "臺灣男演員",
           0.07853875803243504
         ],
         [
           "客家裔臺灣人",
           0.07775312164574238
         ],
         [
           "臺灣作曲家",
           0.06795213648026219
         ],
         [
           "臺灣億萬富豪",
           0.06205651770108215
         ],
         [
           "臺灣新教徒",
           0.06011534659254377
         ],
         [
           "以臺灣音樂家命名的分類",
           0.04864802203579143
         ],
         [
           "臺灣電視主持人",
           0.04471306738037418
         ],
         [
           "叱吒樂壇我最喜愛的歌曲得主",
           0.035176987895887926
         ],
         [
           "全球華語歌曲排行榜最受歡迎男歌手",
           0.03386244943947794
         ],
         [
           "金曲獎演奏類最佳專輯製作人獎獲得者",
           0.03333042924853456
         ],
         [
           "華語流行音樂歌手",
           0.027811995551754405
         ]
       ],
       "key": "周杰倫"
     }

Evaluate

python3 manage.py evaluate --lang <zh or other supported language>

Contributors

• 張泰瑋 david

License

This package use GPL3.0 License.

KCEM experiments

kcem有兩個參數，kcm取幾個、kem取幾個，本實驗使用google的知識圖譜約500筆做測試

為了畫成二維的圖，把kcm的參數表示成顏色、loss為y軸、kem數量為x軸

參數的範圍從2~30 range(2, 30, 2)

1. 舊的kcem跟取第一段維基百科去斷詞，而且不是紀錄頻率而是用set儲存所做出來的kcem效果的比較
2. hybrid的loss V.S. kcem的loss:
3. hybrid 的loss V.S. new method的loss:
4. 四種版本的kcem比較: 同一種方法但是不同kcm、kem參數的loss都畫成同一顏色的線
5. 四種全部都取平均: 同一種方法但是不同kcm、kem參數的loss都取平均,畫成同一顏色的線

10/13小結論：

new method因為只取第1段的表現比較不穩定，所以採用hybrid方法

new method相關的實驗程式放在new_kcem_method

將用hybrid的min：kcm:22 kem:12 loss:21.458033917027294 這組參數當作目前最佳的is-a去做後續應用