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

misc.xml

modules.xml