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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10625/49746
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| Title: | A New Approach for Multi-Document Update Summarization |
| Authors: | Long, Chong Huang, Min-Lie Zhu, Xiao-Yan Li, Ming |
| Keywords: | DATA MINING TEXT MINING KOLMOGOROV COMPLEXITY INFORMATION DISTANCE |
| Issue Date: | 2010 |
| Citation: | Long, C., Huang, M., Zhu, X., & Li, M. (2010). A New Approach for Multi-Document Update Summarization. Journal of Computer Science and Technology, 25 (4): 739-749. doi: 10.1007/s11390-010-9361-x |
| 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. |
| URI: | http://hdl.handle.net/10625/49746 |
| ISSN: | 1000-9000 |
| 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: | 2010-2019 / Années 2010-2019 Breaking the barriers to Internet access / Faire tomber les obstacles entravant l’accès à Internet IDRC Research Results / Résultats de recherches du CRDI
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