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pro vyhledávání: '"Dayanne Gouveia Coelho"'
Autor:
Marcos André Gonçalves, Anisio Lacerda, Dayanne Gouveia Coelho, Reinaldo Silva Fortes, Daniel Xavier de Sousa
Publikováno v:
Information Sciences. 572:558-573
Recommender Systems (RSs) make personalized suggestions of relevant items to users. However, the concept of relevance may involve different quality aspects (objectives), such as accuracy, novelty, and diversity. In addition, users may have their own
Autor:
Marcos André Gonçalves, Dayanne Gouveia Coelho, Carlos Bruckner, Reinaldo Silva Fortes, Anisio Lacerda, Alan R. R. de Freitas
Publikováno v:
UMAP (Adjunct Publication)
Multi-Objective Recommender Systems (MO-RS) consider several objectives to produce useful recommendations. Besides accuracy, other important quality metrics include novelty and diversity of recommended lists of items. Previous research up to this poi
Autor:
Ricardo H. C. Takahashi, António Gaspar-Cunha, Elizabeth F. Wanner, Dayanne Gouveia Coelho, Eduardo G. Carrano
Publikováno v:
Repositório Institucional da UFOP
Universidade Federal de Ouro Preto (UFOP)
instacron:UFOP
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Universidade Federal de Ouro Preto (UFOP)
instacron:UFOP
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
This paper presents a new class of operators for multiobjective evolutionary algorithms that are inspired on feedback-control techniques. The proposed operators, the archive-set reduction and the surface-filling crossover, have the purpose of enhanci
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbbaaf31d20bcb9b74da5f147e77af58
http://www.repositorio.ufop.br/handle/123456789/7018
http://www.repositorio.ufop.br/handle/123456789/7018