Mohammed Salem BinwahlanNaomie SalimLadda Suanmali2025-03-102025-03-102009Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)364210682X; 978-364210682-81611334910.1007/978-3-642-10684-2_242-s2.0-76249095452https://repository.dusit.ac.th//handle/123456789/5046Automatic text summarization systems aim to make their created summaries closer to human summaries. The summary creation under the condition of the redundancy and the summary length limitation is a challenge problem. The automatic text summarization system which is built based on exploiting of the advantages of different techniques in form of an integrated model could produce a good summary for the original document. In this paper, we introduced an integrated model for automatic text summarization problem; we tried to exploit different techniques advantages in building of our model like advantage of diversity based method which can filter the similar sentences and select the most diverse ones and advantage of the differentiation between the most important features and less important using swarm based method. The experimental results showed that our model got the best performance over all methods used in this study. © 2009 Springer-Verlag Berlin Heidelberg.Binary treeDiversityMMISummarizationSummarySwarmConference paperScopus