Possibility and necessity measures for relevance assessment

dc.citation.epage162
dc.citation.spage155
dc.contributor.authorBessai, Fatma-Zohra
dc.contributor.authorBoughanem, M.
dc.date.accessioned2013-11-24T10:35:51Z
dc.date.available2013-11-24T10:35:51Z
dc.date.issued2007-11-09
dc.description.abstractThe major question raised in information retrieval on semi-structured documents relates to the manner of effectively handling the structure and the contents of the document for better answering the user's needs. These needs can be formulated by queries composed of only key words or key words and structural constraints. In this paper, we are interested in Information Retrieval in semi-structured document like XML. For these purposes, we present a model for the semi-structured information retrieval, based on the possibilistic networks. The document - elements and elements - terms relations are modelled by measures of possibility and necessity. In this model, the user's query starts a process of propagation to recover documents or portions of documents necessarily or at least possibly relevant. An example of such a research is proposed in order to illustrate the presented approach.fr_FR
dc.identifier.isbn978-1-59593-832-9
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/300
dc.publisherACMfr_FR
dc.relation.ispartofProceedings of the First Ph.D. Workshop in CIKM, PIKM 2007, Sixteenth ACM Conference on Information and Knowledge Management (PIKM '07 )
dc.relation.ispartofseriesPIKM '07 : Proceedings of the First Ph.D. Workshop in CIKM, PIKM 2007, Sixteenth ACM Conference on Information and Knowledge Management;
dc.relation.pages155-162fr_FR
dc.relation.placeLisbon, Portugalfr_FR
dc.rights.holderACM New York, NY, USAfr_FR
dc.structureSystèmes et Documents Multimédia Structurés (SDMS)fr_FR
dc.subjectSemi-structured Information Retrievalfr_FR
dc.subjectXML documentfr_FR
dc.subjectPossibilistic theoryfr_FR
dc.subjectPossibilistic networkfr_FR
dc.subjectIndexingfr_FR
dc.titlePossibility and necessity measures for relevance assessmentfr_FR
dc.typeConference paper
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