A context-sensitive manifold ranking approach to query-focused multi-document summarization

Xiaoyan Cai; Wenjie Li

doi:10.1007/978-3-642-15246-7_6

A context-sensitive manifold ranking approach to query-focused multi-document summarization

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

7 Citations (Scopus)

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.

Original language	English
Title of host publication	PRICAI 2010
Subtitle of host publication	Trends in Artificial Intelligence - 11th Pacific Rim International Conference on Artificial Intelligence, Proceedings
Pages	27-38
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-642-15246-7_6
Publication status	Published - 3 Nov 2010
Event	11th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2010 - Daegu, Korea, Republic of Duration: 30 Aug 2010 → 2 Sept 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6230 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2010
Country/Territory	Korea, Republic of
City	Daegu
Period	30/08/10 → 2/09/10

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

More information

10.1007/978-3-642-15246-7_6

Cite this

Cai, X., & Li, W. (2010). A context-sensitive manifold ranking approach to query-focused multi-document summarization. In PRICAI 2010: Trends in Artificial Intelligence - 11th Pacific Rim International Conference on Artificial Intelligence, Proceedings (pp. 27-38). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6230 LNAI). https://doi.org/10.1007/978-3-642-15246-7_6

Cai, Xiaoyan ; Li, Wenjie. / A context-sensitive manifold ranking approach to query-focused multi-document summarization. PRICAI 2010: Trends in Artificial Intelligence - 11th Pacific Rim International Conference on Artificial Intelligence, Proceedings. 2010. pp. 27-38 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

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Cai, X & Li, W 2010, A context-sensitive manifold ranking approach to query-focused multi-document summarization. in PRICAI 2010: Trends in Artificial Intelligence - 11th Pacific Rim International Conference on Artificial Intelligence, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6230 LNAI, pp. 27-38, 11th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2010, Daegu, Korea, Republic of, 30/08/10. https://doi.org/10.1007/978-3-642-15246-7_6

A context-sensitive manifold ranking approach to query-focused multi-document summarization. / Cai, Xiaoyan; Li, Wenjie.
PRICAI 2010: Trends in Artificial Intelligence - 11th Pacific Rim International Conference on Artificial Intelligence, Proceedings. 2010. p. 27-38 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6230 LNAI).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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Cai X, Li W. A context-sensitive manifold ranking approach to query-focused multi-document summarization. In PRICAI 2010: Trends in Artificial Intelligence - 11th Pacific Rim International Conference on Artificial Intelligence, Proceedings. 2010. p. 27-38. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-15246-7_6

A context-sensitive manifold ranking approach to query-focused multi-document summarization

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