Graph-based multi-modality learning for topic-focused multi-document summarization

Authors:
Xiaojun Wan;Jianguo Xiao
Affiliations:
Institute of Computer Science and Technology, Peking University, Beijing, China;Institute of Computer Science and Technology, Peking University, Beijing, China
Venue:
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Year:
2009

Citing 18
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Abstract

Graph-based manifold-ranking methods have been successfully applied to topic-focused multi-document summarization. This paper further proposes to use the multi-modality manifold-ranking algorithm for extracting topic-focused summary from multiple documents by considering the within-document sentence relationships and the cross-document sentence relationships as two separate modalities (graphs). Three different fusion schemes, namely linear form, sequential form and score combination form, are exploited in the algorithm. Experimental results on the DUC benchmark datasets demonstrate the effectiveness of the proposed multi-modality learning algorithms with all the three fusion schemes.