Title :
Automatic text summarization based on multi-agent particle swarm optimization
Author :
Asgari, Hamed ; Masoumi, Behrooz ; Sheijani, Omid Sojoodi
Author_Institution :
Dept. of Comput. & Inf. Technol. Eng., Islamic Azad Univ., Qazvin, Iran
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 amount of information, extractive text summarization would be arisen as an NP-complete problem. To solve these problems, metaheuristic algorithms are used. In this paper, a method based on multi-agent particle swarm optimization approach is proposed to improve the extractive text summarization. In this method, each particle will be upgraded with the status of multi-agent systems. The proposed method is tested on DUC 2002 standard documents and analyzed by ROUGE evaluation software. The experimental results show that this method has better performance than other compared methods.
Keywords :
multi-agent systems; particle swarm optimisation; text analysis; DUC 2002 standard documents; NP-complete problem; ROUGE evaluation software; automatic text summarization; document abstract; extractive text summarization improvement; meta-heuristic algorithms; multiagent particle swarm optimization; objective text extraction; particle upgrade; Computers; Data mining; Equations; Information technology; Mathematical model; Particle swarm optimization; Software; Extractive method; Multi-Agent Systems; Particle swarm optimization; Text summarization;
Conference_Titel :
Intelligent Systems (ICIS), 2014 Iranian Conference on
Conference_Location :
Bam
Print_ISBN :
978-1-4799-3350-1
DOI :
10.1109/IranianCIS.2014.6802592
