def main():
# 输入压缩比
ratio = raw_input("Please enter the compressed ratio: ")
title, paragraghs = load_data("data/01.txt")
sentences = []
# 构建文本的句子顺序
for paragragh in paragraghs:
sentences.extend(sentence_cut(paragragh, punctuation_list='!！。'))
sentences_with_indices = dict(zip(sentences, range(len(sentences))))
# 抽取关键词，并计算句子的权重
keywords = get_key_words(title, paragraghs)
key_sentences = compute_sentences_weigths(keywords, paragraghs)
# 根据压缩比，计算需要抽取多少个句子
topK = int(len(key_sentences) * float(ratio))
result_dict = {}
for sentence in key_sentences[:topK]:
result_dict[sentence] = sentences_with_indices[sentence]
# 将抽取出来的句子按原文顺序排好输出
result_dict = sorted(result_dict.iteritems(), key=lambda d: d[1])
result_dict = [result[0] for result in result_dict]
summary = ''.join(result_dict)
print summary
def get_key_sentences(content_weights, content, p_weight=1.2, s_bias=1, s_weight = 1.2):
sentences = sentence_cut(content, punctuation_list='!！。')
for i in range(s_bias):
content_weights[sentences[i]] = {'weight': 0, 'p_weight': p_weight, 's_weight':s_weight}
content_weights[sentences[-i-1]] = {'weight': 0, 'p_weight': p_weight, 's_weight': s_weight}
for sentence in sentences[s_bias:-s_bias]:
content_weights[sentence] = {'weight': 0, 'p_weight': p_weight, 's_weight':1}
return content_weights
def compute_sentences_weigths(keywords, paragraphs, p_bias=1, p_weight=1.2, s_bias=1, s_weight = 1.2):
content_weights = {}
for i in range(p_bias):
content_weights = get_key_sentences(content_weights, paragraphs[i], p_weight=p_weight, s_bias=s_bias, s_weight =s_weight)
content_weights = get_key_sentences(content_weights, paragraphs[-i-1], p_weight=p_weight, s_bias=s_bias, s_weight =s_weight)
for paragraph in paragraphs[p_bias:-p_bias]:
content_weights = get_key_sentences(content_weights, paragraph, p_weight=1, s_bias=s_bias, s_weight =s_weight)
for sentence in content_weights.keys():
for word in keywords.keys():
if word in sentence:
content_weights[sentence]['weight'] += keywords[word]
inner_num = len(sentence_cut(sentence, punctuation_list=',;，:：；… '))
content_weights[sentence] = content_weights[sentence]['weight']*\
content_weights[sentence]['p_weight']*content_weights[sentence]['s_weight']/inner_num
content_weights = sorted(content_weights.iteritems(), key=lambda d: d[1], reverse=True)
content_weights = [list(result)[0] for result in content_weights]
return content_weights
def main():
with codecs.open("data/01.txt", 'r', encoding='GBK') as fr:
sentences = []
for line in fr.readlines():
line = line.strip()
if line:
sentences.extend(sentence_cut(line, punctuation_list='。！!'))
words, text = get_keywords(sentences, ['ns', 'nr', 'n'])
weights = construct_matrix(words)
num = len(text)
start_tr = np.ones((1, num))
d = 0.85
iters = 100
tr = textrank(start_tr, iters, d, weights).tolist()[0]
ratio = float(raw_input("Please enter the compressed ratio: "))
topK = int(num * ratio)
summary = summaly(text, tr, topK)
print summary
def main():
with codecs.open("data/01.txt", 'r', encoding='GBK') as fr:
sentences = []
for line in fr.readlines():
line = line.strip()
if line:
sentences.extend(sentence_cut(line, punctuation_list='。！!'))
words, text = get_keywords(sentences,['ns', 'nr', 'n'])
weights = construct_matrix(words)
num = len(text)
start_tr = np.ones((1,num))
d = 0.85
iters = 100
tr = textrank(start_tr, iters, d, weights).tolist()[0]
ratio = float(raw_input("Please enter the compressed ratio: "))
topK = int(num*ratio)
summary = summaly(text, tr, topK)
print summary