Please use this identifier to cite or link to this item: http://hdl.handle.net/10625/49748
Title: Multi-document Summarization by Information Distance
Authors: Long, C
Huang, M L
Zhu, X Y
Li, M
Keywords: DOCUMENT SUMMARIZATION
CLUSTER ANALYSIS
INFORMATION DISTANCE
Date: 2009
Citation: Long, C., Huang, M. L., Zhu, X. Y., Li, M. (2009). Multi-document Summarization by Information Distance. Proceedings of the Ninth IEEE International Conference on Data Mining, 2009. ICDM '09, Miami, USA. (p. 866-871). doi: 10.1109/ICDM.2009.107
Abstract: Fast changing knowledge on the Internet can be acquired more efficiently with the help of automatic document summarization and updating techniques. This paper described 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 2007 dataset and the TAC 2008 dataset 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.
ISBN: 978-0-7695-3895-2
978-1-4244-5242-2
ISSN: 1550-4786
URI: http://hdl.handle.net/10625/49748
Project Number: 104519
Project Title: International Research Chairs Initiative (IRCI)
Access Restriction: Due to copyright restrictions the full text of this research output is not available in the IDRC Digital Library or by request from the IDRC Library. / Compte tenu des restrictions relatives au droit d`auteur, le texte intégral de cet extrant de recherche n`est pas accessible dans la Bibliothèque numérique du CRDI, et il n`est pas possible d`en faire la demande à la Bibliothèque du CRDI.
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