TF-IDF计算 Python

def ComputeFreq(wordlist, text):
result = []
for word in wordlist:
countword = text.count(word)
texted = nltk.word_tokenize(text)
length = len(texted)
freq = countword/length
temp = {}
temp['word'] = word
temp['freq'] = freq
#print freq
result.append(temp)
return result

def Computetfidf(wordfreq, corpus):
result = []
for item in wordfreq:
word = item['word']
tf = item['freq']
dlength = len(corpus)
count = 1
for line in corpus:
if line.find(word)!=-1:
count = count+1
idf = math.log10(dlength/count)
tfidf = tf*idf
#         tempword.append(word)
#         temptfidf.append(tfidf)
temp = {}
temp['word'] = word
temp['tfidf'] = tfidf
result.append(temp)
result.sort(lambda x,y : -cmp(x['tfidf'], y['tfidf']))
return result

第一个函数：计算word在text的词频

wordlist是list格式的word，text是对应的document，python中的string格式

第二个函数：计算word在语料库中的TF-IDF

wordfreq是第一个函数的输出结果，corpus是document的list存储格式