Multi-Document Summarization Based on Improved Features and Clustering

摘要：

Abstract: Multi-Document summarization is an emerging technique for understanding the main purpose of many documents about the same topic. This paper proposes a new feature selection method to improve the summarization result. When calculating similarity, we use a modified TFIDF formula which achieves a better result. We adopt two ways for exactly extracting keywords. Experimental results demonstrate that our improved method performs better than the traditional one.

关键词： Multi-document summarization feature selection cluster sentence selection

作者: Ying XIONG Hongyan LIU Lei LI

作者单位: Beijing University of Posts and　Telecommunications　Beijing, China

会议类型: 国际会议

会议名称: The 6th International Conference on Natural Language Processing and Knowledge Engineering(第六届IEEE自然语言处理与知识工程国际会议 NLP-KE 2010)

会议地点: 北京

会议语种:英文

页码: 1-5

在线出版日期: 2010-08-21（万方平台首次上网日期，不代表论文的发表时间）