gensim文档：
https://radimrehurek.com/gensim/tutorial.html
安装
pip install gensim
代码示例
# -*- coding: utf-8 -*- import logging import jieba from gensim import corpora, models, similarities logging.basicConfig(level=logging.DEBUG) jieba.setLogLevel(logging.INFO) class DocumentSimilar(object): def __init__(self, documents): self.documents = documents self.dictionary = None self.tfidf = None self.similar_matrix = None self.calculate_similar_matrix() @staticmethod def split_word(document): """ 分词，去除停用词 """ stop_words = {":", "的", "，", "”"} text = [] for word in jieba.cut(document): if word not in stop_words: text.append(word) logging.debug(text) return text def calculate_similar_matrix(self): """ 计算相似度矩阵及一些必要数据 """ words = [self.split_word(document) for document in self.documents] self.dictionary = corpora.Dictionary(words) corpus = [self.dictionary.doc2bow(word) for word in words] self.tfidf = models.TfidfModel(corpus) corpus_tfidf = self.tfidf[corpus] self.similar_matrix = similarities.MatrixSimilarity(corpus_tfidf) def get_similar(self, document): """ 计算要比较的文档与语料库中每篇文档的相似度 """ words = self.split_word(document) corpus = self.dictionary.doc2bow(words) corpus_tfidf = self.tfidf[corpus] return self.similar_matrix[corpus_tfidf] if __name__ == '__main__': documents = [ "货运物流供应商Flexport完成10亿美元融资", "一笔300亿并购落地，一个新游戏帝国崛起", "讯轻科技”累计完成近千万元融资", "窝趣公寓完成近2亿元B轮融资主打品质和轻松社交的居住环境", "IBM的区块链副总裁JesseLund:比特币将达到100万美元", ] doc_similar = DocumentSimilar(documents) # 要比较的文档 new_doc = "窝趣公寓完成近2亿元B轮融资" for value, document in zip(doc_similar.get_similar(new_doc), documents): print("{:.2f}".format(value), document)
输出结果
0.03 货运物流供应商Flexport完成10亿美元融资 0.00 一笔300亿并购落地，一个新游戏帝国崛起 0.10 讯轻科技”累计完成近千万元融资 0.66 窝趣公寓完成近2亿元B轮融资主打品质和轻松社交的居住环境 0.00 IBM的区块链副总裁JesseLund:比特币将达到100万美元
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