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

Rasim M. Alguliev, Ramiz M. Aliguliyev, Chingiz A. Mehdiyev
<span title="">2011</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fqn7ak2nbjc6xgzv2ya3jeam4m" style="color: black;">Applied Computational Intelligence and Soft Computing</a> </i> &nbsp;
Extractive multidocument summarization is modeled as a modifiedp-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
more &raquo; ... oward 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.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2011/351498">doi:10.1155/2011/351498</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/knxw7xqnjva2hcbnlucdxza7hq">fatcat:knxw7xqnjva2hcbnlucdxza7hq</a> </span>
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