A New Approach for Multi-Document Update Summarization |
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Authors: | Chong Long Min-Lie Huang Xiao-Yan Zhu Ming Li |
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Affiliation: | (1) Institute of Computer Science &; Technology, Peking University, Beijing, 100871, China |
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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 (, ) 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. |
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Keywords: | |
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