gSVD++: supporting implicit feedback on recommender systems with metadata awareness (2013)
- Autor:
- Autor USP: MANZATO, MARCELO GARCIA - ICMC
- Unidade: ICMC
- Subjects: MULTIMÍDIA INTERATIVA; WORLD WIDE WEB
- Language: Inglês
- Imprenta:
- ISBN: 9781450316569
- Source:
- Título do periódico: Proceedings
- Conference titles: Symposium on Applied Computing - SAC
-
ABNT
MANZATO, Marcelo Garcia. gSVD++: supporting implicit feedback on recommender systems with metadata awareness. 2013, Anais.. New York: ACM, 2013. . Acesso em: 15 maio 2024. -
APA
Manzato, M. G. (2013). gSVD++: supporting implicit feedback on recommender systems with metadata awareness. In Proceedings. New York: ACM. -
NLM
Manzato MG. gSVD++: supporting implicit feedback on recommender systems with metadata awareness. Proceedings. 2013 ;[citado 2024 maio 15 ] -
Vancouver
Manzato MG. gSVD++: supporting implicit feedback on recommender systems with metadata awareness. Proceedings. 2013 ;[citado 2024 maio 15 ] - Incorporating semantic item representations to soften the cold start problem
- Uma arquitetura de personalização de conteúdo baseada em anotações do usuário
- Similarity-based matrix factorization for item cold-start in recommender systems
- Combining multiple metadata types in movies recommendation using ensemble algorithms
- Exploiting multimodal interactions in recommender systems with ensemble algorithms
- Case recommender: a recommender framework
- Extended recommendation-by-explanation
- Metadata in movies recommendation: a comparison among different approaches
- A collaborative filtering approach based on user's reviews
- Multimodal interactions in recommender systems: an ensembling approach
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