Abstract
Query-focused multi-document summarization aims to create a compressed summary biased to a given query. This paper presents a context-sensitive approach based on manifold ranking of sentences to this summarization task. The proposed context enhanced manifold ranking approach not only looks at the sentence itself, but also considers its surrounding contextual information. Compared to the existing manifold ranking approach which totally ignores the contextual information of a sentence, this approach can capture more additional relevant information which is especially necessary for formulating the relationships between short text snippets like sentences. Experiments are conducted on the DUC 2005 and DUC 2006 data sets and the ROUGE evaluation results demonstrate the advantages of the proposed approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Wan, X.J., Yang, J.W., Xiao, J.G.: Manifold-ranking based topic-focused multi-document summarization. In: Proceedings of 20th International Joint Conference on Artificial Intelligence, pp. 2903–2908 (2007)
Barzilay, R., Mckeown, K.R.: Sentence Fusion for Multi-document News Summarization. Comput. Linguist. 31(3), 297–327 (2005)
Radev, D.R., Jing, H.Y., Stys, M., Tam, D.: Centroid-based summarization of multiple documents. Information Processing and Management 40, 919–938 (2004)
Erkan, G., Radev, D.R.: LexRank: Graph-based centrality as salience in text summarization. Journal of Artificial Intelligence Research 22, 457–479 (2004)
Mihalcea, R.: Graph-based ranking algorithms for sentence extraction, applied to text summarization. In: Proceedings of ACL (2004)
Saggion, H., Bontcheva, K., Cunningham, H.: Robust generic and query-based summarization. In: EACL 2003, pp. 235–238 (2003)
Conroy, J.M., Schlesinger, J.D.: CLASSY query-based multi-document summarization. In: DUC 2005 (2005)
Otterbacher, J., Erkan, G., Radev, D.R.: Using Random Walks for Question-focused Sentence Retrieval. In: HLT/EMNLP 2005, pp. 915–922 (2005)
Zhou, D.Y., Bousquet, O., Lal, T.N., Weston, J., Scholkopf, B.: Learning with local and global consistency. In: Proceedings of 18th NIPS (2003)
Zhou, D.Y., Weston, J., Gretton, A., Bousquet, O., Scholkopf, B.: Ranking on data manifolds. In: Proceedings of 18th NIPS (2003)
Lin, C.Y.: ROUGE: A package for automatic evaluation of summaries. In: Proceedings of workshop on text summarization branches out, post-conference workshop of ACL 2004 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cai, X., Li, W. (2010). A Context-Sensitive Manifold Ranking Approach to Query-Focused Multi-document Summarization. In: Zhang, BT., Orgun, M.A. (eds) PRICAI 2010: Trends in Artificial Intelligence. PRICAI 2010. Lecture Notes in Computer Science(), vol 6230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15246-7_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-15246-7_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15245-0
Online ISBN: 978-3-642-15246-7
eBook Packages: Computer ScienceComputer Science (R0)