A Comprehensive Method for Text Summarization Based on Latent Semantic Analysis

摘要：

　　Text summarization aims at getting the most important content in a condensed form from a given document while retains the semantic information of the text to a large extent.It is considered to be an effective way of tackling information overload.There exist lots of text summarization approaches which are based on Latent Semantic Analysis (LSA).However, none of the previous methods consider the term description of the topic.In this paper, we propose a comprehensive LSA-based text summarization algorithm that combines term description with sentence description for each topic.We also put forward a new way to create the term by sentence matrix.The effectiveness of our method is proved by experimental results.On the summarization performance, our approach obtains higher ROUGE scores than several well known methods.

关键词： Text Summarization Latent Semantic Analysis Singular Value Decomposition

作者: Yingjie Wang Jun Ma

作者单位: School of Computer Science and Technology, Shandong University, Jinan, China

会议类型: 国际会议

会议名称: Second CCF Conference,NLPCC2013(第二届自然语言处理与中文计算会议)

会议地点: 重庆

会议语种:英文

页码: 394-401

在线出版日期: 2013-11-15（万方平台首次上网日期，不代表论文的发表时间）