Python使用gensim计算文档相似性

pre_file.py

    #-*-coding:utf-8-*-
    import MySQLdb
    import MySQLdb as mdb
    import os,sys,string
    import jieba
    import codecs
    reload(sys)
    sys.setdefaultencoding('utf-8')
    #连接数据库
    try:
      conn=mdb.connect(host='127.0.0.1',user='root',passwd='kongjunli',db='test1',charset='utf8')
    except Exception,e:
      print e
      sys.exit()
    #获取cursor对象操作数据库
    cursor=conn.cursor(mdb.cursors.DictCursor) #cursor游标
    #获取内容
    sql='SELECT link,content FROM test1.spider;'
    cursor.execute(sql)   #execute()方法，将字符串当命令执行
    data=cursor.fetchall()#fetchall()接收全部返回结果行
    f=codecs.open('C:\Users\kk\Desktop\hello-result1.txt','w','utf-8')

    for row in data:    #row接收结果行的每行数据
      seg='/'.join(list(jieba.cut(row['content'],cut_all='False')))
      f.write(row['link']+' '+seg+'\r\n')
    f.close()

    cursor.close()
          #提交事务，在插入数据时必须

jiansuo.py

    #-*-coding:utf-8-*-
    import sys
    import string
    import MySQLdb
    import MySQLdb as mdb
    import gensim
    from gensim import corpora,models,similarities
    from gensim.similarities import MatrixSimilarity
    import logging
    import codecs
    reload(sys)
    sys.setdefaultencoding('utf-8')

    con=mdb.connect(host='127.0.0.1',user='root',passwd='kongjunli',db='test1',charset='utf8')
    with con:
      cur=con.cursor()
      cur.execute('SELECT * FROM cutresult_copy')
      rows=cur.fetchall()
      class MyCorpus(object):
        def __iter__(self):
          for row in rows:
            yield str(row[1]).split('/')
    #开启日志
    logging.basicConfig(format='%(asctime)s:%(levelname)s:%(message)s',level=logging.INFO)
    Corp=MyCorpus()
    #将网页文档转化为tf-idf
    dictionary=corpora.Dictionary(Corp)
    corpus=[dictionary.doc2bow(text) for text in Corp] #将文档转化为词袋模型
    #print corpus
    tfidf=models.TfidfModel(corpus)#使用tf-idf模型得出文档的tf-idf模型
    corpus_tfidf=tfidf[corpus]#计算得出tf-idf值
    #for doc in corpus_tfidf:
      #print doc
    ###
    '''
    q_file=open('C:\Users\kk\Desktop\q.txt','r')
    query=q_file.readline()
    q_file.close()
    vec_bow=dictionary.doc2bow(query.split(' '))#将请求转化为词带模型
    vec_tfidf=tfidf[vec_bow]#计算出请求的tf-idf值
    #for t in vec_tfidf:
     # print t
    '''
    ###
    query=raw_input('Enter your query:')
    vec_bow=dictionary.doc2bow(query.split())
    vec_tfidf=tfidf[vec_bow]
    index=similarities.MatrixSimilarity(corpus_tfidf)
    sims=index[vec_tfidf]
    similarity=list(sims)
    print sorted(similarity,reverse=True)

encodings.xml

    <?xml version="1.0" encoding="UTF-8"?>
    <project version="4">
     <component name="Encoding">
      <file url="PROJECT" charset="UTF-8" />
     </component>
    </project>

misc.xml

    <?xml version="1.0" encoding="UTF-8"?>
    <project version="4">
     <component name="ProjectLevelVcsManager" settingsEditedManually="false">
      <OptionsSetting value="true" id="Add" />
      <OptionsSetting value="true" id="Remove" />
      <OptionsSetting value="true" id="Checkout" />
      <OptionsSetting value="true" id="Update" />
      <OptionsSetting value="true" id="Status" />
      <OptionsSetting value="true" id="Edit" />
      <ConfirmationsSetting value="0" id="Add" />
      <ConfirmationsSetting value="0" id="Remove" />
     </component>
     <component name="ProjectRootManager" version="2" project-jdk-name="Python 2.7.11 (C:\Python27\python.exe)" project-jdk-type="Python SDK" />
    </project>

modules.xml

    <?xml version="1.0" encoding="UTF-8"?>
    <project version="4">
     <component name="ProjectModuleManager">
      <modules>
       <module fileurl="file://$PROJECT_DIR$/.idea/爬虫练习代码.iml" filepath="$PROJECT_DIR$/.idea/爬虫练习代码.iml" />
      </modules>
     </component>
    </project>