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尝试用这篇post: http://www.matrix67.com/blog/archives/5044 中的方法实现的一个自动中文抽词算法的Python程序
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# -*- coding=utf-8 -*- | |
import feedparser | |
import re | |
import collections | |
import math | |
def info_entropy(words): | |
result = 0 | |
total = sum([val for _, val in words.iteritems()]) | |
for word, cnt in words.iteritems(): | |
p = float(cnt) / total | |
result -= p * math.log(p) | |
return result | |
max_word_len = 5 | |
entropy_threshold = 1 | |
content = [] | |
articles = feedparser.parse('http://www.liyaos.com/blog/feed') | |
for article in articles.entries: | |
content.append(article.title) | |
content.extend(re.split('<.*?>| ', article.description, 0, re.UNICODE)) | |
content = u''.join(content) | |
sentences = re.split("\W+|[a-zA-Z0-9]+", content, 0, re.UNICODE) | |
freq = collections.Counter() | |
for sentence in sentences: | |
if sentence: | |
l = len(sentence) | |
wl = min(l, max_word_len) | |
for i in range(1, wl + 1): | |
for j in range(0, l - i + 1): | |
freq[sentence[j:j + i]] += 1 | |
total = sum([val for _, val in freq.iteritems()]) | |
ps = collections.defaultdict(int) | |
for word, val in freq.iteritems(): | |
ps[word] = float(val) / total | |
words = set() | |
for word, word_p in ps.items(): | |
if len(word) > 1: | |
p = 0 | |
for i in range(1, len(word)): | |
t = ps[word[0:i]] * ps[word[i:]] | |
p = max(p, t) | |
if freq[word] >= 3 and word_p / p > 100: | |
words.add(word) | |
final_words = set() | |
for word in words: | |
lf = rf = True | |
left_words = collections.Counter() | |
right_words = collections.Counter() | |
pattern = re.compile(word.join(['.?', '.?'])) | |
for sentence in sentences: | |
l = pattern.findall(sentence) | |
if l: | |
if l[0][0:len(word)] != word: | |
left_words[l[0][0]] += 1 | |
else: | |
lf = False | |
if l[0][-1 - len(word):] != word: | |
right_words[l[0][-1]] += 1 | |
else: | |
rf = False | |
left_info_entropy = info_entropy(left_words) | |
right_info_entropy = info_entropy(right_words) | |
if lf and len(left_words) > 0 and left_info_entropy < entropy_threshold: | |
continue | |
if rf and len(right_words) > 0 and right_info_entropy < entropy_threshold: | |
continue | |
final_words.add(word) | |
words_list = list(final_words) | |
words_list.sort(cmp = lambda x, y: cmp(freq[y], freq[x])) | |
for word in words_list: | |
print word.encode('utf8'), freq[word] |
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