Case recommender: a flexible and extensible Python framework for recommender systems (2018)
- Authors:
- USP affiliated authors: MANZATO, MARCELO GARCIA - ICMC ; CAMPELLO, RICARDO JOSÉ GABRIELLI BARRETO - ICMC
- Unidade: ICMC
- DOI: 10.1145/3240323.3241611
- Subjects: SISTEMAS DE INFORMAÇÃO; RECONHECIMENTO DE PADRÕES; PYTHON
- Keywords: Recommender Systems; Framework
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- Conference titles: ACM Conference on Recommender Systems - RecSys
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
COSTA, Arthur da et al. Case recommender: a flexible and extensible Python framework for recommender systems. 2018, Anais.. New York: ACM, 2018. Disponível em: https://doi.org/10.1145/3240323.3241611. Acesso em: 02 out. 2024. -
APA
Costa, A. da, Fressato, E., Neto, F., Manzato, M. G., & Campello, R. J. G. B. (2018). Case recommender: a flexible and extensible Python framework for recommender systems. In Proceedings. New York: ACM. doi:10.1145/3240323.3241611 -
NLM
Costa A da, Fressato E, Neto F, Manzato MG, Campello RJGB. Case recommender: a flexible and extensible Python framework for recommender systems [Internet]. Proceedings. 2018 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1145/3240323.3241611 -
Vancouver
Costa A da, Fressato E, Neto F, Manzato MG, Campello RJGB. Case recommender: a flexible and extensible Python framework for recommender systems [Internet]. Proceedings. 2018 ;[citado 2024 out. 02 ] Available from: https://doi.org/10.1145/3240323.3241611 - Ensemble clustering approaches applied in group-based collaborative filtering supported by multiple users' feedback
- Boosting collaborative filtering with an ensemble of co-trained recommenders
- Exploiting different users' interactions for profiles enrichment in recommender systems
- CoRec: a co-training approach for recommender systems
- Group-based collaborative filtering supported by multiple users' feedback to improve personalized ranking
- Uma arquitetura de personalização de conteúdo baseada em anotações do usuário
- Incorporating semantic item representations to soften the cold start problem
- A unified framework of density-based clustering for semi-supervised classification
- Robust expansion of uncertain Volterra kernels into orthonormal series
- An introduction to models based on Laguerre, Kautz and other related orthonormal functions - part I: linear and uncertain models
Informações sobre o DOI: 10.1145/3240323.3241611 (Fonte: oaDOI API)
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