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dc.contributor.authorAbouzakhar, Nasser
dc.contributor.authorAllison , Ben
dc.contributor.authorGuthrie, Louise
dc.date.accessioned2013-01-14T11:29:14Z
dc.date.available2013-01-14T11:29:14Z
dc.date.issued2008
dc.identifier.citationAbouzakhar , N , Allison , B & Guthrie , L 2008 , Unsupervised Learning-based Anomalous Arabic Text Detection . in Procs 6th Language Resources and Evaluation Conference : LREC 2008 . pp. 291-296 , 6th edition of the Language Resources and Evaluation Conference , Marrakech , Morocco , 28/05/08 .
dc.identifier.citationconference
dc.identifier.otherPURE: 1405986
dc.identifier.otherPURE UUID: 259ce3ae-a3b4-4c2a-8407-7621e7f20285
dc.identifier.otherScopus: 84861397345
dc.identifier.urihttp://hdl.handle.net/2299/9605
dc.description.abstractThe growing dependence of modern society on the Web as a vital source of information and communication has become inevitable. However, the Web has become an ideal channel for various terrorist organisations to publish their misleading information and send unintelligible messages to communicate with their clients as well. The increase in the number of published anomalous misleading information on the Web has led to an increase in security threats. The existing Web security mechanisms and protocols are not appropriately designed to deal with such recently developed problems. Developing technology to detect anomalous textual information has become one of the major challenges within the NLP community. This paper introduces the problem of anomalous text detection by automatically extracting linguistic features from documents and evaluating those features for patterns of suspicious and/or inconsistent information in Arabic documents. In order to achieve that, we defined specific linguistic features that characterise various Arabic writing styles. Also, the paper introduces the main challenges in Arabic processing and describes the proposed unsupervised learning model for detecting anomalous Arabic textual information.en
dc.language.isoeng
dc.relation.ispartofProcs 6th Language Resources and Evaluation Conference
dc.rights/dk/atira/pure/core/openaccesspermission/open
dc.subjectNatural language processing
dc.subjectArabic text processing
dc.subjectAnomalous text detection
dc.subjectUnsupervised learning
dc.titleUnsupervised Learning-based Anomalous Arabic Text Detectionen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
dc.relation.schoolSchool of Computer Science
dc.description.versiontypeFinal Published version
rioxxterms.versionVoR
rioxxterms.versionVoR
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeopenAccess


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