关键词: 关键词扩展, 相近文本, 自动摘要, 图算法, 系统实现

Abstract: This paper proposes an automatic summarization method of news texts using keywords expansion. This method extracts texts with similar topics from large-scale data for input text to form background data, and based on background data this method makes keywords expansion so that keywords can play more important role in guiding summary sentences and consequently improves the quality of news text summarization. The study and experiments show that the results obtained in Rouge-1 and Rouge-2 evaluations are better than those of methods based on keyword, TextRank and Manifold Ranking. This paper constructs a Chinese evaluation set which covers 100 news texts divided into 4 groups, and also develops keyword-based Chinese news text automatic summarization system and Chinese news text automatic evaluation system based on ROUGE theory. Through these systems, the theory put forward in the paper is realized and tested successfully.

Key words: keyword expansion, similar topic text, automatic summarization, graph algorithm, system implementation