关键词: 多文档摘要, 主题模型, 重要主题

Abstract: This paper proposes a multi-document summarization algorithm based on significance topic of LDA (latent Dirichlet allocation) model. There are two differences between this algorithm and other algorithms based on LDA model. Firstly, this algorithm gives the definition of significant topic, divides topic into significance topic and insignificance topic, calculates similarity between sentence and document using significance topic. Secondly, beside topic characteristics, this algorithm also considers some statistics characteristics, such as term frequency, sentence position, sentence length, etc. This algorithm not only highlights the advantages of statistics characteristics, but also cooperates with LDA topic model. The experiments show that the proposed algorithm achieves better performance compared to the other state-of-the-art algorithms on DUC2002 corpus.

Key words: multi-document summarization, topic model, significance topic