基于加权TextRank的中文自动文本摘要

现有中文自动文本摘要方法主要是利用文本自身信息，其缺陷是不能充分利用词语之间的语义相关等信息。鉴于此，提出了一种改进的中文文本摘要方法。此方法将外部语料库信息用词向量的形式融入到TextRank算法中，通过TextRank与word2vec的结合，把句子中每个词语映射到高维词库形成句向量。充分考虑了句子之间的相似度、关键词的覆盖率和句子与标题的相似度等因素，以此计算句子之间的影响权重，并选取排序最靠前的句子重新排序作为文本的摘要。实验结果表明，此方法在本文数据集中取得了较好的效果，自动提取中文摘要的效果比原方法好。

Chinese automatic text summarization based on weighted TextRank

The method of Chinese existing automatic text summarization mainly utilizes the text''s own information, and its defect is that it cannot make full use of the related semantic information between the words. Therefore, this paper proposed an improved Chinese text summarization method. This method integrated the information of the external corpora into the TextRank algorithm in the form of a word vector. Combined TextRank with word2vec, it mapped each word in the sentence to the highdimensional lexicon to form a sentence vector. This method fully considered the similarity between sentences, the coverage of keywords and the similarity between sentence and title to calculate the influence weights among sentences, and choose the top-ranked sentences used as the summarization of the text. The results of experiment show that this method has achieved good results in the data set of this paper, and is more effective than the original method in extracting Chinese summarization automatically.