Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/5350
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dc.contributor.authorSalhi, Ali
dc.contributor.authorYahya, Adnan
dc.date.accessioned2018-02-27T07:18:21Z
dc.date.available2018-02-27T07:18:21Z
dc.date.issued2017-11-11
dc.identifier.issn1865-0937
dc.identifier.urihttp://hdl.handle.net/20.500.11889/5350
dc.description.abstractDocument similarity is basic for Information Retrieval. Cross Lin- gual (CL) similarity is important for many data processing tasks such as CL palgiarism detection and retrieval and document quality assessment. We study CL similarity based on the Explicit Semantic Association (ESA) adapted to a cross lingual setting with focus on Arabic. We compare the degree to which CL similarity testing performs where one of the language is Arabic with its monolingual counterpart for various text chunk sizes. We describe the used infrastructure and report on some of the testing results, study the possible sources of encountered weaknesses and point to the possible directions for improvement.en_US
dc.language.isoen_USen_US
dc.publisherSpringer Verlagen_US
dc.relation.ispartofseriesCommunications in Computer and Information Science #782
dc.subjectCross-language information retrievalen_US
dc.subjectExplicit Semantic Associationen_US
dc.subjectSimilarity (Language learning)en_US
dc.subjectInformation retrieval - Arab countriesen_US
dc.subject.lcshSemantics - Network analysis
dc.titleDocument similarity for Arabic and cross-lingual Web contenten_US
dc.typeArticleen_US
newfileds.departmentEngineering and Technologyen_US
newfileds.conferenceInternational Conference on Arabic Language Processing (6th : 2017 : Morocco)en_US
newfileds.item-access-typebzuen_US
newfileds.thesis-prognoneen_US
newfileds.general-subjectComputers and Information Technology | الحاسوب وتكنولوجيا المعلوماتen_US
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