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dc.contributor.authorSnášel, Václav
dc.contributor.authorKrömer, Pavel
dc.contributor.authorOwais, Suhail S. J.
dc.contributor.authorNyongesa, Henry O.
dc.contributor.authorMaleki-Dizaji, S.
dc.date.accessioned2007-10-10T13:11:15Z
dc.date.available2007-10-10T13:11:15Z
dc.date.issued2007
dc.identifier.citationNeural Network World. 2007, vol. 17, issue 4, p. 321-334.en
dc.identifier.issn1210-0552
dc.identifier.urihttp://hdl.handle.net/10084/63504
dc.language.isoenen
dc.publisherAkademie věd České republiky, Ústav informatikyen
dc.relation.ispartofseriesNeural Network Worlden
dc.subjectsearchen
dc.subjectuser modelingen
dc.subjectsearch query optimizationen
dc.subjectgenetic algorithmsen
dc.titleEvolutionary improving World Wide Web queriesen
dc.typearticleen
dc.identifier.locationNení ve fondu ÚKen
dc.description.abstract-enAs the volume and variety of information sources, especially on the World Wide Web (WWW), continue to grow, the requirements imposed on search applications are steadily increasing. The amount of available data is growing and so do the user demands. Search application should provide the users with accurate, sensible responses to their requests. It is difficult to provide information that accurately matches user information needs. Search effectiveness can be seen as the accuracy of matching user information needs against the retrieved information. There are problems emerging: users often do not present search queries in the form that optimally represents their information need, the measure of a document's relevance is often highly subjective between different users, and information sources might contain heterogeneous documents, in multiple formats and the representation of documents is not unified. This contribution presents a proposal to improve web search effectiveness via evolutionary optimization of the Boolean and vector search queries based on individual user models.en
dc.identifier.wos000249076100006


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