Automatic Text Summarization Based on Multi-Agent Particle Swarm Optimization
Publish place: 12th Iranian Conference on Intelligent Systems
Publish Year: 1392
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICS12_258
تاریخ نمایه سازی: 11 مرداد 1393
Abstract:
Text summarization is the objective extraction of some parts of the text, such as sentence and paragraph, as the document abstract. If there are documents with a large amountof information, extractive text summarization would be arisen as an NP-complete problem. To solve these problems, metaheuristicalgorithms are used. In this paper, a method based on multi-agent particle swarm optimization approach is proposed toimprove the extractive text summarization. In this method, eachparticle will be upgraded with the status of multi-agent systems. The proposed method is tested on DUC 2002 standard documentsand analyzed by ROUGE evaluation software. The experimental results show that this method has better performance than other compared methods
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Authors
Hamed Asgari
Department of Computer and Information Technology Engineering Science and Research Branch, Islamic Azad University, Qazvin, Iran
Behrooz Masoumi
Department of Computer and Information Technology Engineering Qazvin Islamic Azad University Qazvin, Iran
Omid sojoodi sheijani
Department of Computer and Information Technology Engineering Qazvin Islamic Azad University Qazvin, Iran
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