Leveraging hybrid recommenders with multifaceted implicit feedback (2015)
- Authors:
- USP affiliated authors: MANZATO, MARCELO GARCIA - ICMC ; GOULARTE, RUDINEI - ICMC
- School: ICMC
- Subjects: ENGENHARIA DE SOFTWARE; SISTEMAS DE INFORMAÇÃO; WORLD WIDE WEB; SISTEMAS MULTIMÍDIA
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Journal of Universal Computer Science
- ISSN: 0948-695X
- Volume/Número/Paginação/Ano: v. 21, n. 2, p. 223-247, 2015
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ABNT
MANZATO, Marcelo Garcia e SANTOS JUNIOR, Edson B e GOULARTE, Rudinei. Leveraging hybrid recommenders with multifaceted implicit feedback. Journal of Universal Computer Science, v. 21, n. 2, p. 223-247, 2015Tradução . . Disponível em: http://www.jucs.org/jucs_21_2/leveraging_hybrid_recommenders_with/jucs_21_02_0223_0247_manzato.pdf. Acesso em: 19 ago. 2022. -
APA
Manzato, M. G., Santos Junior, E. B., & Goularte, R. (2015). Leveraging hybrid recommenders with multifaceted implicit feedback. Journal of Universal Computer Science, 21( 2), 223-247. Recuperado de http://www.jucs.org/jucs_21_2/leveraging_hybrid_recommenders_with/jucs_21_02_0223_0247_manzato.pdf -
NLM
Manzato MG, Santos Junior EB, Goularte R. Leveraging hybrid recommenders with multifaceted implicit feedback [Internet]. Journal of Universal Computer Science. 2015 ; 21( 2): 223-247.[citado 2022 ago. 19 ] Available from: http://www.jucs.org/jucs_21_2/leveraging_hybrid_recommenders_with/jucs_21_02_0223_0247_manzato.pdf -
Vancouver
Manzato MG, Santos Junior EB, Goularte R. Leveraging hybrid recommenders with multifaceted implicit feedback [Internet]. Journal of Universal Computer Science. 2015 ; 21( 2): 223-247.[citado 2022 ago. 19 ] Available from: http://www.jucs.org/jucs_21_2/leveraging_hybrid_recommenders_with/jucs_21_02_0223_0247_manzato.pdf - Personalized collaborative filtering: a neighborhood model based on contextual constraints
- Introducing the concept of "always–welcome recommendations"
- Automatic annotation of tagged content using predefined semantic concepts
- Accelerometers data interoperability: easing interactive applications development
- A multimedia recommender system based on enriched user profiles
- A conceptual architecture with trust consensus to enhance group recommendations
- Evaluating the impact of demographic data on a hybrid recommender model
- Hybrid recommenders: incorporating metadata awareness into latent factor models
- Uma arquitetura de personalização de conteúdo baseada em anotações do usuário
- Incorporating semantic item representations to soften the cold start problem
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