Selection of Information Sources using a Genetic Algorithm

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dc.contributor.authorLebib, Fatma Zohra
dc.contributor.authorDrias, Habiba
dc.contributor.authorMellah, Hakima
dc.date.accessioned2017-01-15T09:32:15Z
dc.date.available2017-01-15T09:32:15Z
dc.date.issued2017-01-02
dc.description.abstractWe address the problem of information sources selection in a context of a large number of distributed sources. We formulate the sources selection problem as a combinatorial optimization problem in order to yield the best set of relevant information sources for a given query. We define a solution as a combination of sources among a huge predefined set of sources. We propose a genetic algorithm to tackle the issue by maximizing the similarity between a selection and the query. Extensive experiments were performed on databases of scientific research documents covering different domains such as computer science and medicine. The results based on the precision measure are very encouraging.fr_FR
dc.identifier.isrnCERIST- DSISM/RR-17-00000002--DZfr_FR
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/877
dc.publisherCERIST
dc.relation.ispartofRapports de recherche internes
dc.relation.placeAlger
dc.structureTechnologies des systèmes Web et multimédia et de gestion de contenufr_FR
dc.subjectbio-inspired methodsfr_FR
dc.subjectgenetic algorithmsfr_FR
dc.subjectinformation sources selectionfr_FR
dc.subjectdistributed information retrievalfr_FR
dc.titleSelection of Information Sources using a Genetic Algorithmfr_FR
dc.typeTechnical Report
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