Publication:
Arabic word stemming algorithms and retrieval effectiveness

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dc.citedby6
dc.contributor.authorSembok T.M.T.en_US
dc.contributor.authorAta B.A.en_US
dc.contributor.authorid9268900400en_US
dc.contributor.authorid36837446100en_US
dc.date.accessioned2023-12-29T07:43:40Z
dc.date.available2023-12-29T07:43:40Z
dc.date.issued2013
dc.description.abstractDocuments retrieval in Information Retrieval Systems (IRS) is generally about retrieving of relevant documents pertaining to information needs. The more the system able to understand the contents of documents the more effective will be the retrieval outcomes. But understanding of the contents is a very complex task. Conventional IRS applies algorithms that can only approximate the meaning of document contents through keywords approach using vector space model. Keywords may be unstemmed or stemmed. When keywords are stemmed and conflated in retrieval process, we are a step forwards in applying semantic technology in IRS. Word stemming is a process in morphological analysis under natural language processing, before syntactic and semantic analysis. We have developed algorithms for Arabic stemming and incorporated it in our experimental system in order to measure retrieval effectiveness. The results have shown that the retrieval effectiveness has increased when stemming is used.en_US
dc.description.natureFinalen_US
dc.identifier.epage1582
dc.identifier.scopus2-s2.0-84887864770
dc.identifier.spage1577
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84887864770&partnerID=40&md5=7dab76731f4eb220f927d55c385e5316
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29940
dc.identifier.volume3 LNECS
dc.pagecount5
dc.sourceScopus
dc.sourcetitleLecture Notes in Engineering and Computer Science
dc.subjectArtificial intelligence
dc.subjectInformation retrieval
dc.subjectNatural language processing
dc.subjectAlgorithms
dc.subjectArtificial intelligence
dc.subjectInformation retrieval systems
dc.subjectNatural language processing systems
dc.subjectSemantics
dc.subjectVector spaces
dc.subjectExperimental system
dc.subjectMorphological analysis
dc.subjectNAtural language processing
dc.subjectRelevant documents
dc.subjectRetrieval effectiveness
dc.subjectRetrieval process
dc.subjectSemantic technologies
dc.subjectVector space models
dc.subjectInformation retrieval
dc.titleArabic word stemming algorithms and retrieval effectivenessen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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