Geodesic Distance based Multi-document Summarization

摘要：

This paper presents a novel extractive approach which takes advantage of geodesic distance for sentence similarity computation to multi-document summarization task. Based on geodesic distance between every two sentences, the text relationship map is constructed. Sentences with higher degree in the map are selected and grouped into clusters. Finally, sentences with highest degree of each cluster are chosen to form the final summary. Experiments on DUC data are performed and the ROUGE evaluation results demonstrate that the proposed approach can be an effective way for multi-document summarization.

关键词： Geodesic distance Cosine angle distance Sentence similarity Manifold Multi-document Summarization

作者: Huifang MA Qing HE Zhongzhi SHI

作者单位: Institute of Computing Technology,Chinese Academy of Sciences;Graduate University of Chinese Academy Institute of Computing Technology,Chinese Academy of Sciences.Beijing,China

会议类型: 国际会议

会议名称: The 2008 IEEE International Conference on Natural Language Processing and Knowledge Engineering(IEEE NLP-KE 2008)(2008IEEE自然语言处理与知识工程国际会议)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-19（万方平台首次上网日期，不代表论文的发表时间）