期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 40, 期 2, 页码 458-465出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2012.07.049
关键词
Constraint-driven summarization; Coverage-driven summarization; Diversity-driven summarization; Quadratic integer programming; Particle swarm optimization
This paper proposes a constraint-driven document summarization approach emphasizing the following two requirements: (1) diversity in summarization, which seeks to reduce redundancy among sentences in the summary and (2) sufficient coverage, which focuses on avoiding the loss of the document's main information when generating the summary. The constraint-driven document summarization models with tuning the constraint parameters can drive content coverage and diversity in a summary. The models are formulated as a quadratic integer programming (QIP) problem. To solve the QIP problem we used a discrete PSO algorithm. The models are implemented on multi-document summarization task. The comparative results showed that the proposed models outperform other methods on DUC2005 and DUC2007 datasets. (C) 2012 Elsevier Ltd. All rights reserved.
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