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This paper proposes a movie genre-prediction based on multinomial probability model.
Resnick, P., & Varian, H. R, ”Recommender systems”, Communications of the ACM,
1997
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Liu, B., Hsu, W., & Chen, S, ”Using General Impressions to Analyze Discovered Classification Rules,” In KDD (pp. 31-36)
1997
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McCallum, A., & Nigam, K, ”A comparison of event models for naive bayes text classification,” In AAAI-98 workshop on learning for text categorization (Vol. 752, pp. 41-48)
1998
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Eyheramendy, S., Lewis, D. D., & Madigan, D, ”On the naive bayes model for text categorization,” In 9th International Workshop on Artificial Intelligence and Statistics,
2003
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Herlocker, J. L., Konstan, J. A., Terveen, L. G., & Riedl, J. T, ”Evaluating collaborative filtering recommender systems,” ACM Transactions on Information Systems (TOIS)
2004
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McNee, S. M., Riedl, J., & Konstan, J. A, ”Being accurate is not enough: how accuracy metrics have hurt recommender systems,” In CHI’06 extended abstracts on Human factors in computing systems (pp. 1097-1101),
2006
Cited alongside, same era.
2007
Cited alongside, same era.
Su, X., & Khoshgoftaar, T. M, ”A survey of collaborative filtering techniques,” Advances in artificial intelligence
2009
Cited alongside, same era.
Amatriain, X., Lathia, N., Pujol, J. M., Kwak, H, & Oliver, N, ”The wisdom of the few: a collaborative filtering approach based on expert opinions from the web,” In Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval (pp. 532-539),
2009
Cited alongside, same era.
Liu, Q., Cheng, B., & Xu, C, ”Collaborative Filtering Based on Star Users,” In Tools with Artificial Intelligence (ICTAI)
2011
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Tuzhilin, A., & Adamopoulos, P, ”Probabilistic Neighborhood Selection in Collaborative Filtering Systems,” Working Paper: CBA-13-04, New York University, 2013
2013
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Vargas, S., Baltrunas, L., Karatzoglou, A., & Castells, P, ”Coverage, redundancy and size-awareness in genre diversity for recommender systems,” In Proceedings of the 8th ACM Conference on Recommender systems (pp. 209-216)
2014
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de Gemmis, M., Lops, P., Semeraro, G., & Musto, C,”An investigation on the serendipity problem in recommender systems,” Information Processing & Management
2015
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Ge, M., Delgado-Battenfeld, C., & Jannach, D,”Beyond accuracy: evaluating recommender systems by coverage and serendipity,” In Proceedings of the fourth ACM conference on Recommender systems (pp. 257-260)
2010
Cited alongside, same era.