Table of Contents Author Guidelines Submit a Manuscript
Applied Computational Intelligence and Soft Computing
Volume 2011, Article ID 351498, 13 pages
Research Article

pSum-SaDE: A Modified p-Median Problem and Self-Adaptive Differential Evolution Algorithm for Text Summarization

Institute of Information Technology of Azerbaijan National Academy of Sciences, B. Vahabzade Street, 9, AZ1141 Baku, Azerbaijan

Received 11 May 2011; Revised 26 July 2011; Accepted 27 August 2011

Academic Editor: Chuan-Kang Ting

Copyright © 2011 Rasim M. Alguliev et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Extractive multidocument summarization is modeled as a modified p-median problem. The problem is formulated with taking into account four basic requirements, namely, relevance, information coverage, diversity, and length limit that should satisfy summaries. To solve the optimization problem a self-adaptive differential evolution algorithm is created. Differential evolution has been proven to be an efficient and robust algorithm for many real optimization problems. However, it still may converge toward local optimum solutions, need to manually adjust the parameters, and finding the best values for the control parameters is a consuming task. In the paper is proposed a self-adaptive scaling factor in original DE to increase the exploration and exploitation ability. This paper has found that self-adaptive differential evolution can efficiently find the best solution in comparison with the canonical differential evolution. We implemented our model on multi-document summarization task. Experiments have shown that the proposed model is competitive on the DUC2006 dataset.