Event-based summarization using critical temporal event term chain

Maofu Liu; Wenjie Li; Xiaolong Zhang; Ji Zhang

doi:10.1007/978-3-642-00831-3_38

Event-based summarization using critical temporal event term chain

Maofu Liu, Wenjie Li, Xiaolong Zhang, Ji Zhang

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

Abstract

In this paper, we investigate whether temporal relations among event terms can help improve event-based summarization and text cohesion of final summaries. By connecting event terms with happens-before relations, we build a temporal event term graph for source documents. The event terms in the critical temporal event term chain identified from the maximal weakly connected component are used to evaluate the sentences in source documents. The most significant sentences are included in final summaries. Experiments conducted on the DUC 2001 corpus show that event-based summarization using the critical temporal event term chain is able to organize final summaries in a more coherent way and make improvement over the well-known tf idf-based and PageRank-based summarization approaches.

Original language	English
Title of host publication	Computer Processing of Oriental Languages
Subtitle of host publication	Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings
Pages	378-385
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-00831-3_38
Publication status	Published - 9 Nov 2009
Event	22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009 - , Hong Kong Duration: 26 Mar 2009 → 27 Mar 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5459 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009
Country/Territory	Hong Kong
Period	26/03/09 → 27/03/09

Keywords

Depth-First Search Algorithm
Event Term Graph
Event-Based Summarization
Temporal Event Term Chain

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

More information

10.1007/978-3-642-00831-3_38

Cite this

Liu, M., Li, W., Zhang, X., & Zhang, J. (2009). Event-based summarization using critical temporal event term chain. In Computer Processing of Oriental Languages: Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings (pp. 378-385). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5459 LNAI). https://doi.org/10.1007/978-3-642-00831-3_38

Liu, Maofu ; Li, Wenjie ; Zhang, Xiaolong ; Zhang, Ji. / Event-based summarization using critical temporal event term chain. Computer Processing of Oriental Languages: Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings. 2009. pp. 378-385 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In this paper, we investigate whether temporal relations among event terms can help improve event-based summarization and text cohesion of final summaries. By connecting event terms with happens-before relations, we build a temporal event term graph for source documents. The event terms in the critical temporal event term chain identified from the maximal weakly connected component are used to evaluate the sentences in source documents. The most significant sentences are included in final summaries. Experiments conducted on the DUC 2001 corpus show that event-based summarization using the critical temporal event term chain is able to organize final summaries in a more coherent way and make improvement over the well-known tf idf-based and PageRank-based summarization approaches.",

keywords = "Depth-First Search Algorithm, Event Term Graph, Event-Based Summarization, Temporal Event Term Chain",

author = "Maofu Liu and Wenjie Li and Xiaolong Zhang and Ji Zhang",

year = "2009",

month = nov,

day = "9",

doi = "10.1007/978-3-642-00831-3_38",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Liu, M, Li, W, Zhang, X & Zhang, J 2009, Event-based summarization using critical temporal event term chain. in Computer Processing of Oriental Languages: Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5459 LNAI, pp. 378-385, 22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009, Hong Kong, 26/03/09. https://doi.org/10.1007/978-3-642-00831-3_38

Event-based summarization using critical temporal event term chain. / Liu, Maofu; Li, Wenjie; Zhang, Xiaolong; Zhang, Ji.

Computer Processing of Oriental Languages: Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings. 2009. p. 378-385 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5459 LNAI).

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

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AU - Li, Wenjie

AU - Zhang, Xiaolong

AU - Zhang, Ji

PY - 2009/11/9

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N2 - In this paper, we investigate whether temporal relations among event terms can help improve event-based summarization and text cohesion of final summaries. By connecting event terms with happens-before relations, we build a temporal event term graph for source documents. The event terms in the critical temporal event term chain identified from the maximal weakly connected component are used to evaluate the sentences in source documents. The most significant sentences are included in final summaries. Experiments conducted on the DUC 2001 corpus show that event-based summarization using the critical temporal event term chain is able to organize final summaries in a more coherent way and make improvement over the well-known tf idf-based and PageRank-based summarization approaches.

AB - In this paper, we investigate whether temporal relations among event terms can help improve event-based summarization and text cohesion of final summaries. By connecting event terms with happens-before relations, we build a temporal event term graph for source documents. The event terms in the critical temporal event term chain identified from the maximal weakly connected component are used to evaluate the sentences in source documents. The most significant sentences are included in final summaries. Experiments conducted on the DUC 2001 corpus show that event-based summarization using the critical temporal event term chain is able to organize final summaries in a more coherent way and make improvement over the well-known tf idf-based and PageRank-based summarization approaches.

KW - Depth-First Search Algorithm

KW - Event Term Graph

KW - Event-Based Summarization

KW - Temporal Event Term Chain

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SN - 9783642008306

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Liu M, Li W, Zhang X, Zhang J. Event-based summarization using critical temporal event term chain. In Computer Processing of Oriental Languages: Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings. 2009. p. 378-385. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-00831-3_38

Event-based summarization using critical temporal event term chain

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ASJC Scopus subject areas

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