Metalearning and recommender systems: a literature review and empirical study on the algorithm selection problem for collaborative filtering (2018)
- Authors:
- Autor USP: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.ins.2017.09.050
- Subjects: APRENDIZADO COMPUTACIONAL; RECONHECIMENTO DE PADRÕES; ALGORITMOS
- Keywords: Metalearning; Algorithm selection; Recommendation system; Collaborative Filtering
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Information Sciences
- ISSN: 0020-0255
- Volume/Número/Paginação/Ano: v. 423, p. 128-144, Jan. 2018
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
- Licença: other-oa
-
ABNT
CUNHA, Tiago e SOARES, Carlos e CARVALHO, André Carlos Ponce de Leon Ferreira de. Metalearning and recommender systems: a literature review and empirical study on the algorithm selection problem for collaborative filtering. Information Sciences, v. 423, n. Ja 2018, p. 128-144, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2017.09.050. Acesso em: 26 abr. 2024. -
APA
Cunha, T., Soares, C., & Carvalho, A. C. P. de L. F. de. (2018). Metalearning and recommender systems: a literature review and empirical study on the algorithm selection problem for collaborative filtering. Information Sciences, 423( Ja 2018), 128-144. doi:10.1016/j.ins.2017.09.050 -
NLM
Cunha T, Soares C, Carvalho ACP de LF de. Metalearning and recommender systems: a literature review and empirical study on the algorithm selection problem for collaborative filtering [Internet]. Information Sciences. 2018 ; 423( Ja 2018): 128-144.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1016/j.ins.2017.09.050 -
Vancouver
Cunha T, Soares C, Carvalho ACP de LF de. Metalearning and recommender systems: a literature review and empirical study on the algorithm selection problem for collaborative filtering [Internet]. Information Sciences. 2018 ; 423( Ja 2018): 128-144.[citado 2024 abr. 26 ] Available from: https://doi.org/10.1016/j.ins.2017.09.050 - Reduction strategies for hierarchical multi-label classification in protein function prediction
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Informações sobre o DOI: 10.1016/j.ins.2017.09.050 (Fonte: oaDOI API)
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