Mining unstructured content for recommender systems: an ensemble approach (2016)
Source: Information Retrieval Journal. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, RECONHECIMENTO DE TEXTO, WORLD WIDE WEB
ABNT
MANZATO, Marcelo Garcia et al. Mining unstructured content for recommender systems: an ensemble approach. Information Retrieval Journal, v. 19, n. 4, p. 378-415, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10791-016-9280-8. Acesso em: 21 out. 2024.APA
Manzato, M. G., Domingues, M. A., Fortes, A. C., Sundermann, C. V., D'Addio, R. M., Conrado, M. S., et al. (2016). Mining unstructured content for recommender systems: an ensemble approach. Information Retrieval Journal, 19( 4), 378-415. doi:10.1007/s10791-016-9280-8NLM
Manzato MG, Domingues MA, Fortes AC, Sundermann CV, D'Addio RM, Conrado MS, Rezende SO, Pimentel M da GC. Mining unstructured content for recommender systems: an ensemble approach [Internet]. Information Retrieval Journal. 2016 ; 19( 4): 378-415.[citado 2024 out. 21 ] Available from: https://doi.org/10.1007/s10791-016-9280-8Vancouver
Manzato MG, Domingues MA, Fortes AC, Sundermann CV, D'Addio RM, Conrado MS, Rezende SO, Pimentel M da GC. Mining unstructured content for recommender systems: an ensemble approach [Internet]. Information Retrieval Journal. 2016 ; 19( 4): 378-415.[citado 2024 out. 21 ] Available from: https://doi.org/10.1007/s10791-016-9280-8