Topic Modeling Based Text Summarization Approach

摘要：

　　Extracting sentences that contain important information from a passage is a form of text summarization.It is an important research aspect in semantic analysis for academia and industry.However, previous researches do not achieve a satisfying performance since they suffer from curse of dimensionality.This paper proposes an approach which solves the problem by topic modeling.Experiment results on 2 web blog datasets show that comparing with previous methods, our topic modeling based approach improves the precision of text summarization by 10%.

关键词： Text Summarization Topic Modeling LDA Semantic Analysis

作者: Shusi Yu Wei Wang

作者单位: IT Operation Center Shanghai Branch of China Telecom Corporation Limited, Shanghai, China

会议类型: 国际会议

会议名称: International Conference on Computational Science and Engineering Applications(CSEA2015)2015计算机科学与工程应用国际会议

会议地点: 三亚

会议语种:英文

页码: 203-207

在线出版日期: 2015-12-26（万方平台首次上网日期，不代表论文的发表时间）