Intelligent model for automatic text summarization

dc.contributor.authorM.S. Binwahlan
dc.contributor.authorN. Salim
dc.contributor.authorL. Suanmali
dc.date.accessioned2025-03-10T07:38:08Z
dc.date.available2025-03-10T07:38:08Z
dc.date.issued2009
dc.description.abstractThe navigation through hundreds of the documents in order to find the interesting information is a tough job and waste of the time and effort. Automatic text summarization is a technique concerning the creation of a compressed form for single document or multi-documents for tackling such problem. In this study, we introduced an intelligent model for automatic text summarization problem; we tried to exploit different resources 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 non diversity method used in this study which is the adaptation of intelligent techniques like fuzzy logic and swarm intelligence for building that method which gave it a good ability for picking up the most important sentences in the text. The experimental results showed that our model got the best performance over all methods used in this study. © 2009 Asian Network for Scientific Information.
dc.identifier.citationInformation Technology Journal
dc.identifier.doi10.3923/itj.2009.1249.1255
dc.identifier.issn18125646
dc.identifier.scopus2-s2.0-70349662279
dc.identifier.urihttps://repository.dusit.ac.th//handle/123456789/5068
dc.languageEnglish
dc.rightsAll Open Access; Bronze Open Access
dc.rights.holderScopus
dc.subjectBinary tree
dc.subjectDiversity
dc.subjectFuzzy
dc.subjectSummarization
dc.subjectSummary
dc.subjectSwarm
dc.titleIntelligent model for automatic text summarization
dc.typeArticle
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-70349662279&doi=10.3923%2fitj.2009.1249.1255&partnerID=40&md5=70f0a43412e05ee5c702f2305b597ffd
oaire.citation.endPage1255
oaire.citation.issue8
oaire.citation.startPage1249
oaire.citation.volume8
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