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HitsAlgo API documentation.html
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<article id="content">
<header>
<h1 class="title">Module <code>HitsAlgo</code></h1>
</header>
<section id="section-intro">
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python hljs"><span class="hljs-comment">#!/usr/bin/env python</span>
<span class="hljs-comment"># coding: utf-8</span>
<span class="hljs-comment"># In[1]:</span>
<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
<span class="hljs-keyword">import</span> networkx <span class="hljs-keyword">as</span> nx
<span class="hljs-keyword">from</span> nltk.corpus <span class="hljs-keyword">import</span> stopwords
<span class="hljs-keyword">from</span> nltk.stem <span class="hljs-keyword">import</span> WordNetLemmatizer
lemmatizer = WordNetLemmatizer()
<span class="hljs-keyword">import</span> matplotlib.pyplot <span class="hljs-keyword">as</span> plt
<span class="hljs-keyword">import</span> time
<span class="hljs-keyword">import</span> collections
<span class="hljs-keyword">import</span> scipy <span class="hljs-keyword">as</span> sp
<span class="hljs-comment"># In[2]:</span>
<span class="hljs-string">"""Taking the given graph as input into G"""</span>
G = nx.read_gpickle(<span class="hljs-string">"web_graph.gpickle"</span>)
G
<span class="hljs-comment"># In[3]:</span>
G.nodes[<span class="hljs-number">0</span>][<span class="hljs-string">'page_content'</span>]
<span class="hljs-comment"># In[4]:</span>
<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">draw</span>(<span class="hljs-params">G</span>):</span>
<span class="hljs-string">""" This function is to draw the graph"""</span>
pos = {i: G.nodes[i][<span class="hljs-string">'pos'</span>] <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> range(len(G.nodes))}
nx.draw(G, pos,with_labels=<span class="hljs-literal">True</span>)
<span class="hljs-comment"># In[5]:</span>
len(G.nodes)
<span class="hljs-string">"""Edges present in the graph"""</span>
G.edges
<span class="hljs-comment"># In[6]:</span>
<span class="hljs-string">""" Adjacency Matrix for the given graph G"""</span>
Adj = nx.adjacency_matrix(G)
Adj
<span class="hljs-comment"># In[7]:</span>
Adj = Adj.todense()
<span class="hljs-comment"># In[8]:</span>
Adj
<span class="hljs-comment"># In[9]:</span>
Adj = np.array(Adj)
Adj
<span class="hljs-comment"># In[10]:</span>
<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">get_words</span>(<span class="hljs-params">st</span>):</span>
<span class="hljs-string">"""This is the preprocessing step which gives the words in the corpus removing corpus\n
Stopwords removal and lemmatization is done on the data\n
:param
data in the document/query
:returns
List of words after performing the preprocessing on data
"""</span>
st = st.lower()
st = <span class="hljs-string">''</span>.join(ch <span class="hljs-keyword">for</span> ch <span class="hljs-keyword">in</span> st <span class="hljs-keyword">if</span> ch.isalnum() <span class="hljs-keyword">or</span> ch==<span class="hljs-string">' '</span>)
words = st.split()
stpwrds = set(stopwords.words(<span class="hljs-string">'english'</span>))
newwords = set()
<span class="hljs-keyword">for</span> word <span class="hljs-keyword">in</span> words:
word = lemmatizer.lemmatize(word)
<span class="hljs-keyword">if</span> word <span class="hljs-keyword">not</span> <span class="hljs-keyword">in</span> stpwrds <span class="hljs-keyword">and</span> word != <span class="hljs-string">' '</span> <span class="hljs-keyword">and</span> word !=<span class="hljs-string">''</span> :
newwords.add(word)
newwords = list(newwords)
<span class="hljs-keyword">if</span> len(newwords) == <span class="hljs-number">0</span>:
print(<span class="hljs-string">"True"</span>)
<span class="hljs-keyword">return</span> newwords
<span class="hljs-comment"># In[11]:</span>
<span class="hljs-string">"""This generate the posting list from the given data"""</span>
posting_list = {}
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> range(len(G.nodes)):
doc = G.nodes[i][<span class="hljs-string">'page_content'</span>]
words = get_words(doc)
<span class="hljs-keyword">for</span> word <span class="hljs-keyword">in</span> words:
s = posting_list.get(word, <span class="hljs-literal">None</span>)
<span class="hljs-keyword">if</span> s <span class="hljs-keyword">is</span> <span class="hljs-literal">None</span>:
s = set()
posting_list[word] = s
s.add(i)
<span class="hljs-comment"># In[12]:</span>
<span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">hits_algo</span>(<span class="hljs-params">query</span>):</span>
<span class="hljs-string">""" Words from the given query are lemmalizedand stored in qwords\n
Base Set and Root set for the given query are generated\n
Sub graph of the given graph is taken with nodes present in the BaseSet\n
Adjacency matrix A is generated for the obtained subgraph\n
Eigen vectors and Eigen values are generated for A.A^T and A^T.A \n
The principal eigen vector of AA^T gives the hub scores and the principal eigen vector of A^T.A gives us the Authority scores of the nodes\n
The nodes are then ordered according to their corresponding velues in the eigen vector\n
This print the hubs and authorities in decreasing Scores\n
:param
This take given query as parameter
:returns
list of processing time and the number of edges
"""</span>
start = time.time()
qwords = get_words(query)
<span class="hljs-keyword">if</span>(len(qwords)!=<span class="hljs-number">0</span>):
posting_list.get(query,<span class="hljs-literal">None</span>)
rootSet = posting_list.get(qwords[<span class="hljs-number">0</span>],set()).copy()
<span class="hljs-keyword">for</span> word <span class="hljs-keyword">in</span> qwords:
rootSet = rootSet.intersection(posting_list.get(word,set()))
baseSet = rootSet.copy()
<span class="hljs-keyword">for</span> node <span class="hljs-keyword">in</span> rootSet:
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> range(len(Adj[<span class="hljs-number">0</span>])):
<span class="hljs-keyword">if</span> Adj[node][i] == <span class="hljs-number">1</span>:
baseSet.add(i)
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> range(len(Adj)):
<span class="hljs-keyword">for</span> node <span class="hljs-keyword">in</span> rootSet:
<span class="hljs-keyword">if</span> Adj[i][node] == <span class="hljs-number">1</span>:
baseSet.add(i)
baseList = list(baseSet)
G1 = G.subgraph(baseList)
nodesList = list(G1.nodes)
A = nx.adjacency_matrix(G1)
A = A.todense()
A = np.array(A)
AAT = A.dot(A.transpose())
ATA = A.transpose().dot(A)
hub,Hubscores = np.linalg.eig(AAT)
index = np.argmax(hub)
Hubscores[:,index] = Hubscores[:,index]/((sum(Hubscores[:,index])))
arr = np.flip((np.argsort(Hubscores[:,index])))
auth,AuthorityScores = np.linalg.eig(ATA)
index = np.argmax(auth)
AuthorityScores[:,index] = AuthorityScores[:,index]/((sum(AuthorityScores[:,index])))
arr1 = np.flip((np.argsort(AuthorityScores[:,index])))
list_h = arr.tolist()
orderOfHub = np.array(nodesList)
orderOfHub[list_h]
print(<span class="hljs-string">"List of nodes with increasing HubScore: "</span> )
print(orderOfHub[list_h])
list1 = arr1.tolist()
orderOfAuthority = np.array(nodesList)
orderOfAuthority[list1]
print(<span class="hljs-string">"List of nodes with increasing AuthorityScore: "</span>)
<span class="hljs-keyword">print</span> (orderOfAuthority[list1])
end = time.time()
time_diff = end - start
print(time_diff)
<span class="hljs-comment">#print("No of edges/links in the subgraph: ")</span>
print(len(G1.edges))
<span class="hljs-keyword">return</span> list([time_diff,len(G1.edges)])
<span class="hljs-comment"># In[29]:</span>
query = input(<span class="hljs-string">"Enter the query : "</span>)
hits_algo(query)
<span class="hljs-comment"># In[ ]:</span>
<span class="hljs-comment"># In[39]:</span>
i=<span class="hljs-number">1</span>
dict1 ={}
<span class="hljs-keyword">for</span> key <span class="hljs-keyword">in</span> posting_list.keys():
<span class="hljs-keyword">if</span>(i><span class="hljs-number">1400</span>):
<span class="hljs-keyword">break</span>
v = hits_algo(key)
dict1[v[<span class="hljs-number">1</span>]]=(v[<span class="hljs-number">0</span>])
i=i+<span class="hljs-number">1</span>
<span class="hljs-comment"># In[40]:</span>
dict1 = collections.OrderedDict(sorted(dict1.items()))
dict1
<span class="hljs-comment"># In[42]:</span>
x = dict1.keys()
y = dict1.values()
<span class="hljs-comment"># Plotting the Graph</span>
plt.plot(x, y)
plt.title(<span class="hljs-string">"Plot of Runtime vs Number of edges"</span>)
plt.xlabel(<span class="hljs-string">"Number Of Edges"</span>)
plt.ylabel(<span class="hljs-string">"Runtime"</span>)
plt.show()
<span class="hljs-comment"># In[ ]:</span>
<span class="hljs-comment"># In[ ]:</span>
<span class="hljs-comment"># In[ ]:</span></code></pre>
</details>
</section>
<section>
</section>
<section>
</section>
<section>
<h2 class="section-title" id="header-functions">Functions</h2>
<dl>
<dt id="HitsAlgo.draw"><code class="name flex">
<span>def <span class="ident">draw</span></span>(<span>G)</span>
</code></dt>
<dd>
<div class="desc"><p>This function is to draw the graph</p></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python hljs"><span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">draw</span>(<span class="hljs-params">G</span>):</span>
<span class="hljs-string">""" This function is to draw the graph"""</span>
pos = {i: G.nodes[i][<span class="hljs-string">'pos'</span>] <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> range(len(G.nodes))}
nx.draw(G, pos,with_labels=<span class="hljs-literal">True</span>)</code></pre>
</details>
</dd>
<dt id="HitsAlgo.get_words"><code class="name flex">
<span>def <span class="ident">get_words</span></span>(<span>st)</span>
</code></dt>
<dd>
<div class="desc"><p>This is the preprocessing step which gives the words in the corpus removing corpus</p>
<p>Stopwords removal and lemmatization is done on the data</p>
<p>:param
data in the document/query
:returns
List of words after performing the preprocessing on data</p></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python hljs"><span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">get_words</span>(<span class="hljs-params">st</span>):</span>
<span class="hljs-string">"""This is the preprocessing step which gives the words in the corpus removing corpus\n
Stopwords removal and lemmatization is done on the data\n
:param
data in the document/query
:returns
List of words after performing the preprocessing on data
"""</span>
st = st.lower()
st = <span class="hljs-string">''</span>.join(ch <span class="hljs-keyword">for</span> ch <span class="hljs-keyword">in</span> st <span class="hljs-keyword">if</span> ch.isalnum() <span class="hljs-keyword">or</span> ch==<span class="hljs-string">' '</span>)
words = st.split()
stpwrds = set(stopwords.words(<span class="hljs-string">'english'</span>))
newwords = set()
<span class="hljs-keyword">for</span> word <span class="hljs-keyword">in</span> words:
word = lemmatizer.lemmatize(word)
<span class="hljs-keyword">if</span> word <span class="hljs-keyword">not</span> <span class="hljs-keyword">in</span> stpwrds <span class="hljs-keyword">and</span> word != <span class="hljs-string">' '</span> <span class="hljs-keyword">and</span> word !=<span class="hljs-string">''</span> :
newwords.add(word)
newwords = list(newwords)
<span class="hljs-keyword">if</span> len(newwords) == <span class="hljs-number">0</span>:
print(<span class="hljs-string">"True"</span>)
<span class="hljs-keyword">return</span> newwords</code></pre>
</details>
</dd>
<dt id="HitsAlgo.hits_algo"><code class="name flex">
<span>def <span class="ident">hits_algo</span></span>(<span>query)</span>
</code></dt>
<dd>
<div class="desc"><p>Words from the given query are lemmalized and stored in qwords</p>
<p>Base Set and Root set for the given query are generated</p>
<p>Sub graph of the given graph is taken with nodes present in the BaseSet</p>
<p>Adjacency matrix A is generated for the obtained subgraph</p>
<p>Eigen vectors and Eigen values are generated for A.A^T and A^T.A </p>
<p>The principal eigen vector of AA^T gives the hub scores and the principal eigen vector of A^T.A gives us the Authority scores of the nodes</p>
<p>The nodes are then ordered according to their corresponding values in the eigen vector</p>
<p>This print the hubs and authorities in decreasing Scores</p>
<p>:param
This take given query as parameter</p>
<p>:returns
list of processing time and the number of edges</p></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python hljs"><span class="hljs-function"><span class="hljs-keyword">def</span> <span class="hljs-title">hits_algo</span>(<span class="hljs-params">query</span>):</span>
<span class="hljs-string">""" Words from the given query are lemmalizedand stored in qwords\n
Base Set and Root set for the given query are generated\n
Sub graph of the given graph is taken with nodes present in the BaseSet\n
Adjacency matrix A is generated for the obtained subgraph\n
Eigen vectors and Eigen values are generated for A.A^T and A^T.A \n
The principal eigen vector of AA^T gives the hub scores and the principal eigen vector of A^T.A gives us the Authority scores of the nodes\n
The nodes are then ordered according to their corresponding velues in the eigen vector\n
This print the hubs and authorities in decreasing Scores\n
:param
This take given query as parameter
:returns
list of processing time and the number of edges
"""</span>
start = time.time()
qwords = get_words(query)
<span class="hljs-keyword">if</span>(len(qwords)!=<span class="hljs-number">0</span>):
posting_list.get(query,<span class="hljs-literal">None</span>)
rootSet = posting_list.get(qwords[<span class="hljs-number">0</span>],set()).copy()
<span class="hljs-keyword">for</span> word <span class="hljs-keyword">in</span> qwords:
rootSet = rootSet.intersection(posting_list.get(word,set()))
baseSet = rootSet.copy()
<span class="hljs-keyword">for</span> node <span class="hljs-keyword">in</span> rootSet:
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> range(len(Adj[<span class="hljs-number">0</span>])):
<span class="hljs-keyword">if</span> Adj[node][i] == <span class="hljs-number">1</span>:
baseSet.add(i)
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> range(len(Adj)):
<span class="hljs-keyword">for</span> node <span class="hljs-keyword">in</span> rootSet:
<span class="hljs-keyword">if</span> Adj[i][node] == <span class="hljs-number">1</span>:
baseSet.add(i)
baseList = list(baseSet)
G1 = G.subgraph(baseList)
nodesList = list(G1.nodes)
A = nx.adjacency_matrix(G1)
A = A.todense()
A = np.array(A)
AAT = A.dot(A.transpose())
ATA = A.transpose().dot(A)
hub,Hubscores = np.linalg.eig(AAT)
index = np.argmax(hub)
Hubscores[:,index] = Hubscores[:,index]/((sum(Hubscores[:,index])))
arr = np.flip((np.argsort(Hubscores[:,index])))
auth,AuthorityScores = np.linalg.eig(ATA)
index = np.argmax(auth)
AuthorityScores[:,index] = AuthorityScores[:,index]/((sum(AuthorityScores[:,index])))
arr1 = np.flip((np.argsort(AuthorityScores[:,index])))
list_h = arr.tolist()
orderOfHub = np.array(nodesList)
orderOfHub[list_h]
print(<span class="hljs-string">"List of nodes with increasing HubScore: "</span> )
print(orderOfHub[list_h])
list1 = arr1.tolist()
orderOfAuthority = np.array(nodesList)
orderOfAuthority[list1]
print(<span class="hljs-string">"List of nodes with increasing AuthorityScore: "</span>)
<span class="hljs-keyword">print</span> (orderOfAuthority[list1])
end = time.time()
time_diff = end - start
print(time_diff)
<span class="hljs-comment">#print("No of edges/links in the subgraph: ")</span>
print(len(G1.edges))
<span class="hljs-keyword">return</span> list([time_diff,len(G1.edges)])</code></pre>
</details>
</dd>
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<li><h3><a href="file:///C:/Users/balup/PycharmProjects/pythonProject1/pythonProject1/HitsAlgo.html#header-functions">Functions</a></h3>
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<li><code><a title="HitsAlgo.draw" href="file:///C:/Users/balup/PycharmProjects/pythonProject1/pythonProject1/HitsAlgo.html#HitsAlgo.draw">draw</a></code></li>
<li><code><a title="HitsAlgo.get_words" href="file:///C:/Users/balup/PycharmProjects/pythonProject1/pythonProject1/HitsAlgo.html#HitsAlgo.get_words">get_words</a></code></li>
<li><code><a title="HitsAlgo.hits_algo" href="file:///C:/Users/balup/PycharmProjects/pythonProject1/pythonProject1/HitsAlgo.html#HitsAlgo.hits_algo">hits_algo</a></code></li>
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