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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
Issue 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.
URI: http://hdl.handle.net/10625/49748
ISBN: 978-0-7695-3895-2
978-1-4244-5242-2
ISSN: 1550-4786
Project Number: 104519
Project Title: International Research Chairs Initiative (IRCI)
Document Delivery: This document is not available in the IDRC Digital Library / Ce document n'est pas disponible dans la Bibliothèque numérique du CRDI
Appears in Collections:IDRC Research Results / Résultats de recherches du CRDI
Breaking the barriers to Internet access / Faire tomber les obstacles entravant l’accès à Internet
2000-2009 / Années 2000-2009

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