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dc.contributor.authorSilveira Netto Nunes, Maria Augusta
dc.date.accessioned2016-06-27T19:04:09Z
dc.date.available2016-06-27T19:04:09Z
dc.date.created2008-12-12
dc.identifiereprint:380
dc.identifier.urihttp://hdl.handle.net/10919/71621
dc.description.abstractThe World Wide Web is a great source of products and services available to people. Scientists have made a huge effort to create effective strategies to personalize those products/services for anyone willing to use them. The personalization may be provided by Recommender Systems which are able to match people’s preferences to specific products or services. Scientists from different research areas such as Psychology, Neurology and Affective Computing agree that human reasoning and decision-making are hardly ever affected by psychological aspects. Thus, to maintain the same level of personalized service provided by humans, computers should also “reason”, taking into account users’ psychological aspects. Nevertheless, the psychological aspects have, unfortunately, not been highly applied in most models of User Profiles used in Recommender Systems. As a result, the existing Recommender Systems do not actually use psychological aspects such as Personality Traits during their decision-making process in order to generate their recommendations. In this thesis we propose the implementation of the Personality Traits in User Profiles so it is possible to obtain evidence that the use of Personality Traits in Recommender Systems might be coherent and effective for the improvement of the recommendations for users and, therefore, act proactively towards users’ needs, offering more adaptable products and services according to their future needs.en_US
dc.description.sponsorshipCAPES - URI
dc.format.extent142 pagesen_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isofren_US
dc.relation.urihttp://www.lirmm.fr/~nunes/hp/publications/TeseFinal.pdf
dc.subject.lccT1
dc.titleRecommender Systems based on Personality Traitsen_US
dc.typeDissertationen_US
dc.contributor.departmentInformationen_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorUniversité Montpellier 2 - LIRMMen_US
dc.identifier.sourceurlhttp://tel.archives-ouvertes.fr/index.php?halsid=2brvf7qqpebqftghi52t87uie4&view_this_doc=tel-00348370&version=1en_US


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