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Journal of Computer Science and Technology 2010, Vol. 25 Issue (4) :739-749    DOI: 10.1007/s11390-010-1057-8
Special Section on Advances in Machine Learning and Applications Current Issue | Archive | Adv Search << Previous Articles | Next Articles >>
A New Approach for Multi-Document Update Summarization
Chong Long1(龙 翀), Min-Lie Huang1(黄民烈), Xiao-Yan Zhu1,*(朱小燕), Member, CCF and Ming Li2(李 明), Fellow, ACM, IEEE
1. State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China 2. School of Computer Science, University of Waterloo, Waterloo N2L 3G1, Canada

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Abstract 

Fast changing knowledge on the Internet can be acquired more efficiently with the help of automatic document summarization and updating techniques. This paper describes a novel approach for multi-document update summarization. The best summary is defined to be the one which has the minimum information distance to the entire document set. The best update summary has the minimum conditional information distance to a document cluster given that a prior document cluster has already been read. Experiments on the DUC/TAC 2007 to 2009 datasets (http://duc.nist.gov/, http://www.nist.gov/tac/) have proved that our method closely correlates with the human summaries and outperforms other programs such as LexRank in many categories under the ROUGE evaluation criterion.

Articles by authors
Chong Long
Min-Lie Huang
Xiao-Yan Zhu
Ming Li
Keywordsdata mining   text mining   Kolmogorov complexity   information distance     
Received 2009-10-22;
Fund:

The work was supported by the National Natural Science Foundation of China under Grant No. 60973104, the National Basic Research 973 Program of China under Grant No. 2007CB311003, and the IRCI Project from IDRC, Canada.

Cite this article:   
Chong Long(龙 翀), Min-Lie Huang(黄民烈), Xiao-Yan Zhu(朱小燕), Member, CCF and Ming Li(李 明), Fellow, ACM, IEEE.A New Approach for Multi-Document Update Summarization[J]  Journal of Computer Science and Technology, 2010,V25(4): 739-749
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