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A multinomial probabilistic model for movie genre predictions

2016-03-25 · Eric Makita, Artem Lenskiy

This paper proposes a movie genre-prediction based on multinomial probability model. To the best of our knowledge, this problem has not been addressed yet in the field of recommender system. The prediction of a movie genre has many practical applications including complementing the items categories given by experts and providing a surprise effect in the recommendations given to a user. We employ mulitnomial event model to estimate a likelihood of a movie given genre and the Bayes rule to evaluate the posterior probability of a genre given a movie. Experiments with the MovieLens dataset validate our approach. We achieved 70% prediction rate using only 15% of the whole set for training.

📄 PDF Abstract BibTeX arXiv:1603.07849

Code (1)

anahnas/SIAP tf

Tasks

modelPredictionRecommendation Systems

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