A Classification-based XML Information Retrieval Model

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dc.contributor.authorBessai, Fatma-Zohra
dc.date.accessioned2014-12-03T07:59:02Z
dc.date.available2014-12-03T07:59:02Z
dc.date.issued2014-11-27
dc.description.abstractThe main problem of content-based XML information retrieval is how to select the relevant unit of information that answers the user’s query composed of only key words (content only). Our objective is to select relevant elements that can belong to different parts of XML documents of the corpus for user’s information need. To do this, we propose a neural XML information retrieval model using Kohonen self-organizing maps. Kohonen self-organizing map lets classification of XML elements producing density map that form the foundations of the XML information retrieval system.fr_FR
dc.identifier.isrnCERIST-DTISI/RR--14-000000030--dzfr_FR
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/698
dc.publisherCERIST
dc.relation.ispartofRapports de recherche internes
dc.relation.placeAlger
dc.structureRecherche, Filtrage et Traitement Automatique de l'Informationfr_FR
dc.subjectNeural Networksfr_FR
dc.subjectXML Information Retrievalfr_FR
dc.subjectclassification of XML elementsfr_FR
dc.titleA Classification-based XML Information Retrieval Modelfr_FR
dc.typeTechnical Report
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