Automatic Classification and Filtering of Electronic Information: Knowledge-Based Filtering Approach

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dc.citation.epage92fr_FR
dc.citation.issue1fr_FR
dc.citation.spage85fr_FR
dc.citation.volume1fr_FR
dc.contributor.authorNouali, Omar
dc.contributor.authorBlache, Philippe
dc.date.accessioned2013-12-04T15:00:42Z
dc.date.available2013-12-04T15:00:42Z
dc.date.issued2004
dc.description.abstractIn this paper we propose an artificial intelligent approach focusing on information filtering problem. First, we give an overview of the information filtering process and a survey of different models of textual information filtering. Second, we present our E-mail filtering tool. It consists of an expert system in charge of driving the filtering process in cooperation with a knowledge-based model. Neural networks are used to model all system knowledge. The system is based on machine learning techniques to continuously learn and improve its knowledge all along its life cycle. This email filtering tool assists the user in managing, selecting, classify and discarding non-desirable messages in a professional or non-professional context. The modular structure makes it portable and easy to adapt to other filtering applications such as web browsing. The performance of the system is discussed.fr_FR
dc.identifier.e-issn2309-4524
dc.identifier.issn1683-3198
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/463
dc.publisherZarqa Private University, Jordanfr_FR
dc.relation.ispartofThe International Arab Journal of Information Technology (IAJIT)fr_FR
dc.rights.holderZarqa Private Universityfr_FR
dc.subjectInformation filteringfr_FR
dc.subjectExpert systemsfr_FR
dc.subjectMachine learningfr_FR
dc.subjectNeural networksfr_FR
dc.subjectRelevance feedbackfr_FR
dc.subjectGenetic algorithmsfr_FR
dc.titleAutomatic Classification and Filtering of Electronic Information: Knowledge-Based Filtering Approachfr_FR
dc.typeArticle
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