Modeling Document Summarization as Multi-objective Optimization

Authors:
Lei Huang;Yanxiang He;Furu Wei;Wenjie Li
Affiliations:
-;-;-;-
Venue:
IITSI '10 Proceedings of the 2010 Third International Symposium on Intelligent Information Technology and Security Informatics
Year:
2010

Citing 0
Cited 5

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Applied Computational Intelligence and Soft Computing
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CDDS: Constraint-driven document summarization models

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DESAMC+DocSum: Differential evolution with self-adaptive mutation and crossover parameters for multi-document summarization

Knowledge-Based Systems
Multiple documents summarization based on evolutionary optimization algorithm

Expert Systems with Applications: An International Journal

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Abstract

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.