Eliminating redundancy by spectral relaxation for multi-document summarization

Authors:
Fumiyo Fukumoto;Akina Sakai;Yoshimi Suzuki
Affiliations:
University of Yamanashi;University of Yamanashi;University of Yamanashi
Venue:
TextGraphs-5 Proceedings of the 2010 Workshop on Graph-based Methods for Natural Language Processing
Year:
2010

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Abstract

This paper focuses on redundancy, overlapping information in multi-documents, and presents a method for detecting salient, key sentences from documents that discuss the same event. To eliminate redundancy, we used spectral clustering and classified each sentence into groups, each of which consists of semantically related sentences. Then, we applied link analysis, the Markov Random Walk (MRW) Model to deciding the importance of a sentence within documents. The method was tested on the NTCIR evaluation data, and the result shows the effectiveness of the method.