Author:
Cunha Tiago,Soares Carlos,de Carvalho André C. P. L. F.
Publisher
Springer International Publishing
Reference28 articles.
1. Bobadilla, J., Ortega, F., Hernando, A., Gutiérrez, A.: Recommender systems survey. Knowl.-Based Syst. 46, 109–132 (2013)
2. Brazdil, P., Giraud-Carrier, C., Soares, C., Vilalta, R.: Metalearning: Applications to Data Mining, 1st edn. Springer Publishing Company, Incorporated, Heidelberg (2009)
3. Dooms, S., De Pessemier, T., Martens, L.: MovieTweetings: a movie rating dataset collected from twitter. In: Workshop on Crowdsourcing and Human Computation for Recommender Systems, CrowdRec at RecSys 2013 (2013)
4. Gantner, Z., Rendle, S., Freudenthaler, C., Schmidt-Thieme, L.: MyMediaLite: a free recommender system library. In: ACM Conference on Recommender Systems, pp. 305–308 (2011)
5. Goldberg, K., Roeder, T., Gupta, D., Perkins, C.: Eigentaste: a constant time collaborative filtering algorithm. Inf. Retrieval 4(2), 133–151 (2001)
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