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Author Xiaojun Wan ♦ Jianwu Yang ♦ Jianguo Xiao
Sponsorship IEEE Comput. Soc. ♦ WIC ♦ ACM
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2006
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Computer science ♦ Data mining
Abstract Graph-ranking based methods have been developed for generic multi-document summarization in recent years and they make uniform use of the relationships between sentences to extract salient sentences. This paper proposes to integrate the relevance of the sentences to the specified topic into the graph-ranking based method for topic-focused multi-document summarization. The cross-document relationships and the within-document relationships between sentences are differentiated and we apply the graph-ranking based method using each individual kind of sentence relationships and explore their relative importance for topic-focused multi-document summarization. Experimental results on DUC2003 and DUC2005 demonstrate the great importance of the cross-document relationships between sentences for topic-focused multi-document summarization. Even the approach based only on the cross-document sentence relationships can perform better than or at least as well as the approaches based on both kinds of sentence relationships
Description Author affiliation: Inst. of Comput. Sci. & Technol., Peking Univ., Beijing (Xiaojun Wan; Jianwu Yang; Jianguo Xiao)
ISBN 0769527477
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2006-12-18
Publisher Place China
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 267.05 kB
Page Count 7
Starting Page 1012
Ending Page 1018


Source: IEEE Xplore Digital Library