A multinomial probabilistic model for movie genre predictions
Abstract
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.
Cite
@article{arxiv.1603.07849,
title = {A multinomial probabilistic model for movie genre predictions},
author = {Eric Makita and Artem Lenskiy},
journal= {arXiv preprint arXiv:1603.07849},
year = {2016}
}
Comments
5 pages, 4 figures, 8th International Conference on Machine Learning and Computing, Hong Kong