Improving Multidimensional Recommender Systems Using Dimensions as Virtual Items
Referências
Adomavicius, G., Sankaranarayanan, R., Sen, S., and Tuzhilin, A. (2005). Incorporating contextual information in recommender systems using a multidimensional approach. ACM Transactions on Information Systems, 23(1):103–145.
Adomavicius, G. and Tuzhilin, A. (2001a). Extending recommender systems: A multidimensional approach. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-01), Workshop on Intelligent Techniques for Web Personalization (ITWP2001), Seattle, Washington.
Adomavicius, G. and Tuzhilin, A. (2001b). Multidimensional recommender systems: A data warehousing approach. In WELCOM ’01: Proceedings of the Second International Workshop on Electronic Commerce, pages 180–192, London, UK. Springer- Verlag.
Adomavicius, G. and Tuzhilin, A. (2011). Context-aware recommender systems. In Ricci, F., Rokach, L., Shapira, B., and Kantor, P. B., editors, Recommender Systems Handbook, pages 217–253. Springer US.
Anand, S. S. and Mobasher, B. (2003). Intelligent techniques for web personalization. In Intelligent Techniques for Web Personalization (ITWP 2003), LNCS 3169, pages 1–36.
Breese, J. S., Heckerman, D., and Kadie, C. M. (1998). Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, pages 43–52.
Deshpande, M. and Karypis, G. (2004). Item-based top 177.
Domingues, M. A., Jorge, A. M., and Soares, C. (2009). Using contextual information as virtual items on top-n recommender systems. In ACM RecSys’09 Workshop on Context-Aware Recommender Systems (CARS-2009).
Domingues, M. A., Jorge, A. M., and Soares, C. (2013). Dimensions as virtual items: Improving the predictive ability of top-n recommender systems. Inf. Process. Manage., 49(3):698–720.
Linden, G., Smith, B., and York, J. (2003). Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Computing, 7(1):76–80.
Resnick, P. and Varian, H. R. (1997). Recommender systems. Communications of the ACM, 40(3):56–58.
Ricci, F., Rokach, L., Shapira, B., and Kantor, P. B., editors (2011). Recommender Systems Handbook. Springer.
Shani, G. and Gunawardana, A. (2011). Evaluating recommendation systems. In Ricci, F., Rokach, L., Shapira, B., and Kantor, P. B., editors, Recommender Systems Handbook, pages 257–297. Springer US.
Adomavicius, G. and Tuzhilin, A. (2001a). Extending recommender systems: A multidimensional approach. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-01), Workshop on Intelligent Techniques for Web Personalization (ITWP2001), Seattle, Washington.
Adomavicius, G. and Tuzhilin, A. (2001b). Multidimensional recommender systems: A data warehousing approach. In WELCOM ’01: Proceedings of the Second International Workshop on Electronic Commerce, pages 180–192, London, UK. Springer- Verlag.
Adomavicius, G. and Tuzhilin, A. (2011). Context-aware recommender systems. In Ricci, F., Rokach, L., Shapira, B., and Kantor, P. B., editors, Recommender Systems Handbook, pages 217–253. Springer US.
Anand, S. S. and Mobasher, B. (2003). Intelligent techniques for web personalization. In Intelligent Techniques for Web Personalization (ITWP 2003), LNCS 3169, pages 1–36.
Breese, J. S., Heckerman, D., and Kadie, C. M. (1998). Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, pages 43–52.
Deshpande, M. and Karypis, G. (2004). Item-based top 177.
Domingues, M. A., Jorge, A. M., and Soares, C. (2009). Using contextual information as virtual items on top-n recommender systems. In ACM RecSys’09 Workshop on Context-Aware Recommender Systems (CARS-2009).
Domingues, M. A., Jorge, A. M., and Soares, C. (2013). Dimensions as virtual items: Improving the predictive ability of top-n recommender systems. Inf. Process. Manage., 49(3):698–720.
Linden, G., Smith, B., and York, J. (2003). Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Computing, 7(1):76–80.
Resnick, P. and Varian, H. R. (1997). Recommender systems. Communications of the ACM, 40(3):56–58.
Ricci, F., Rokach, L., Shapira, B., and Kantor, P. B., editors (2011). Recommender Systems Handbook. Springer.
Shani, G. and Gunawardana, A. (2011). Evaluating recommendation systems. In Ricci, F., Rokach, L., Shapira, B., and Kantor, P. B., editors, Recommender Systems Handbook, pages 257–297. Springer US.
Publicado
28/07/2014
Como Citar
DOMINGUES, Marcos; JORGE, Alípio; SOARES, Carlos; REZENDE, Solange.
Improving Multidimensional Recommender Systems Using Dimensions as Virtual Items. In: SEMINÁRIO INTEGRADO DE SOFTWARE E HARDWARE (SEMISH), 41. , 2014, Brasília.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2014
.
p. 25-35.
ISSN 2595-6205.
