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dc.contributor.advisorRigo, Sandro José
dc.contributor.authorPizzato, Cleber Beal
dc.date.accessioned2021-10-07T23:46:34Z
dc.date.accessioned2022-09-22T19:45:05Z
dc.date.available2021-10-07T23:46:34Z
dc.date.available2022-09-22T19:45:05Z
dc.date.issued2020-10-09
dc.identifier.urihttps://hdl.handle.net/20.500.12032/64549
dc.description.abstractRecommendation Systems are of great relevance for systems that want to deliver more value to the user. They provide personalized results by the use of particular algorithms. Among the various recommendation techniques the Image Recommendation Systems have become extremely useful since the visual aspect of the items can influence the user’s decision. A recommendation model can be designed to benefit from Social Network data and their interconnection aspects to improve their results. The experiments carried out demonstrate an approach capable of using images from social networks in the construction of a recommendation model and, among other results, finding alternatives to mitigate the cold-start problem.en
dc.publisherUniversidade do Vale do Rio dos Sinospt_BR
dc.subjectSistemas de recomendaçãopt_BR
dc.subjectCold-starten
dc.titleSistemas de recomendação com auxílio de processamento de imagens de redes sociaispt_BR
dc.typeTCCpt_BR


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