Python使用gensim计算文档相似性

 #-*-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:\U<i style="color:transparent">来源gaodai$ma#com搞$$代**码网</i>sers\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 

 #-*-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)