A multi-agent recommender system

Registro completo de metadados
Autor(es): dc.creatorA. Jorge Morais-
Autor(es): dc.creatorOliveira, Eugénio-
Autor(es): dc.creatorJorge, Alípio Mário-
Data de aceite: dc.date.accessioned2019-08-21T17:09:44Z-
Data de disponibilização: dc.date.available2019-08-21T17:09:44Z-
Data de envio: dc.date.issued2017-01-24-
Data de envio: dc.date.issued2017-01-24-
Data de envio: dc.date.issued2012-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/10400.2/5973-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/10400.2/5973-
Descrição: dc.descriptionThe large amount of pages in Websites is a problem for users who waste time looking for the information they really want. Knowledge about users’ previous visits may provide patterns that allow the customization of the Website. This concept is known as Adaptive Website: a Website that adapts itself for the purpose of improving the user’s experience. Some Web Mining algorithms have been proposed for adapting a Website. In this paper, a recommender system using agents with two different algorithms (associative rules and collaborative filtering) is described. Both algorithms are incremental and work with binary data. Results show that this multi-agent approach combining different algorithms is capable of improving user’s satisfaction.-
Descrição: dc.descriptioninfo:eu-repo/semantics/publishedVersion-
Idioma: dc.languageen-
Relação: dc.relationhttp://link.springer.com/chapter/10.1007/978-3-642-28765-7_33-
Direitos: dc.rightsrestrictedAccess-
Título: dc.titleA multi-agent recommender system-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Aberto - Universidade Aberta (Portugal)

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