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01.02.2008

Using only cross-document relationships for both generic and topic-focused multi-document summarizations

verfasst von: Xiaojun Wan

Erschienen in: Discover Computing | Ausgabe 1/2008

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Abstract

In recent years graph-ranking based algorithms have been proposed for single document summarization and generic multi-document summarization. The algorithms make use of the “votings” or “recommendations” between sentences to evaluate the importance of the sentences in the documents. This study aims to differentiate the cross-document and within-document relationships between sentences for generic multi-document summarization and adapt the graph-ranking based algorithm for topic-focused summarization. The contributions of this study are two-fold: (1) For generic multi-document summarization, we apply the graph-based ranking algorithm based on each kind of sentence relationship and explore their relative importance for summarization performance. (2) For topic-focused multi-document summarization, we propose to integrate the relevance of the sentences to the specified topic into the graph-ranking based method. Each individual kind of sentence relationship is also differentiated and investigated in the algorithm. Experimental results on DUC 2002–DUC 2005 data demonstrate the great importance of the cross-document relationships between sentences for both generic and topic-focused multi-document summarizations. Even the approach based only on the cross-document relationships can perform better than or at least as well as the approaches based on both kinds of relationships between sentences.

Vorheriger Artikel An effective and efficient results merging strategy for multilingual information retrieval in federated search environments

Nächster Artikel Nearest-biclusters collaborative filtering based on constant and coherent values

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Titel: Using only cross-document relationships for both generic and topic-focused multi-document summarizations
verfasst von: Xiaojun Wan
Publikationsdatum: 01.02.2008
Verlag: Springer Netherlands
Erschienen in: Discover Computing / Ausgabe 1/2008
Print ISSN: 2948-2984
Elektronische ISSN: 2948-2992
DOI: https://doi.org/10.1007/s10791-007-9037-5

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