MULTI-DOCUMENT SUMMARIZATION SYSTEMS COMPARISON

摘要：

　　This paper compared two multi-document summarization systems we developed.One system used hierarchical sentence clustering algorithm to find the important information,while the other system mainly adopted hierarchical Latent Dirichlet Allocation (hLDA) topic model to obtain the sub-topics of multi-document data.Both of the two systems are evaluated and compared on TAC 2010/TAC 2011 data using the ROUGE testing method with same parameters setting.The results have shown that the hLDA system has got some improvement compared with the clustering system.And normally in ROUGE testing,results from non-stopwords are better than those from stopwords.

关键词： Multi-document summarization System comparison Hierarchical sentence clustering HLDA

作者: Lei Li Wei Heng Pingan Liu

作者单位: School of Computer Science and Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China

会议类型: 国际会议

会议名称: 2012 2nd IEEE International Conference on Cloud Computing and Intelligence Systems (2012年第2届IEEE云计算与智能系统国际会议(IEEE CCIS2012))

会议地点: 杭州

会议语种:英文

页码: 1891-1895

在线出版日期: 2012-10-30（万方平台首次上网日期，不代表论文的发表时间）