Exploiting different users' interactions for profiles enrichment in recommender systems (2016)
- Authors:
- USP affiliated authors: MANZATO, MARCELO GARCIA - ICMC ; CAMPELLO, RICARDO JOSÉ GABRIELLI BARRETO - ICMC
- Unidade: ICMC
- DOI: 10.1145/2851613.2851923
- Subjects: INTELIGÊNCIA ARTIFICIAL; SISTEMAS DE INFORMAÇÃO; WORLD WIDE WEB
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Proceedings
- Conference titles: Symposium on Applied Computing - SAC
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
COSTA, Arthur F. da; MARTINS, Rafael D; MANZATO, Marcelo Garcia; CAMPELLO, Ricardo José Gabrielli Barreto. Exploiting different users' interactions for profiles enrichment in recommender systems. Anais.. New York: ACM, 2016.Disponível em: -
APA
Costa, A. F. da, Martins, R. D., Manzato, M. G., & Campello, R. J. G. B. (2016). Exploiting different users' interactions for profiles enrichment in recommender systems. In Proceedings. New York: ACM. doi:10.1145/2851613.2851923 -
NLM
Costa AF da, Martins RD, Manzato MG, Campello RJGB. Exploiting different users' interactions for profiles enrichment in recommender systems [Internet]. Proceedings. 2016 ;Available from: http://dx.doi.org/10.1145/2851613.2851923 -
Vancouver
Costa AF da, Martins RD, Manzato MG, Campello RJGB. Exploiting different users' interactions for profiles enrichment in recommender systems [Internet]. Proceedings. 2016 ;Available from: http://dx.doi.org/10.1145/2851613.2851923 - Ensemble clustering approaches applied in group-based collaborative filtering supported by multiple users' feedback
- Case recommender: a flexible and extensible Python framework for recommender systems
- Boosting collaborative filtering with an ensemble of co-trained recommenders
- CoRec: a co-training approach for recommender systems
- Group-based collaborative filtering supported by multiple users' feedback to improve personalized ranking
- Incorporating semantic item representations to soften the cold start problem
- Uma arquitetura de personalização de conteúdo baseada em anotações do usuário
- Case recommender: a recommender framework
- Similarity-based matrix factorization for item cold-start in recommender systems
- Combining multiple metadata types in movies recommendation using ensemble algorithms
Informações sobre o DOI: 10.1145/2851613.2851923 (Fonte: oaDOI API)
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Referências citadas na obra
| DOI: 10.1145/2043932.2044016 |
|---|
| DOI: 10.1145/2664551.2664556 |
| DOI: 10.1016/j.is.2012.03.001 |
| DOI: 10.1145/1401890.1401944 |
| Y. Koren. Factor in the neighbors: Scalable and accurate collaborative filtering. ACM Transactions on Knowledge Discovery from Data (TKDD) 4(1):1--24 Jan. 2010. 10.1145/1644873.1644874 Y. Koren. Factor in the neighbors: Scalable and accurate collaborative filtering. ACM Transactions on Knowledge Discovery from Data (TKDD) 4(1):1--24 Jan. 2010. 10.1145/1644873.1644874 |
| DOI: 10.1145/2168752.2168771 |
| Autor: Rendle S. Primeira página: 452 Ano: 2009 |
| DOI: 10.5555/1941884 |
