Modeling Document Summarization as Multi-objective Optimization

In this paper, we consider document summarization as a multi-objective optimization problem involving four objective functions, namely information coverage, significance, redundancy and text coherence. These functions measure the possible summaries based on the identified core terms and main topics...

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Bibliographic Details
Published in2010 Third International Symposium on Intelligent Information Technology and Security Informatics pp. 382 - 386
Main Authors Lei Huang, Yanxiang He, Furu Wei, Wenjie Li
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2010
Subjects
Computer science
Computer security
Data mining
document summarization
Dynamic programming
Greedy algorithms
Inference algorithms
Informatics
Information security
Information technology
multi-objective optimization
Optimization methods
query-sensitive term weighting and clustering
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ISBN9781424467303
1424467306
DOI10.1109/IITSI.2010.80

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Summary:In this paper, we consider document summarization as a multi-objective optimization problem involving four objective functions, namely information coverage, significance, redundancy and text coherence. These functions measure the possible summaries based on the identified core terms and main topics (i.e. a cluster of semantically or statistically related core terms). We choose the DUC 2005 and 2006 query-oriented summarization tasks to exam the proposed model. The encouraging results indicate that the multi-objective optimization based framework for document summarization is truly a promising research direction.
ISBN:9781424467303
1424467306
DOI:10.1109/IITSI.2010.80