Abstract
The digital entertainment sector is one of the fastest growing in recent years. In the case of video games, the productions of some of the most popular titles are on a par with film productions. The sale of video games is in the millions, and yet there are few works on the recommendation of video games. In this work a hybrid system of video game recommendation is presented, through the use of collaborative filtering and content-based filtering, and the construction of relationship graphs. In order to improve the recommendations, a new method for estimating implicit ratings is proposed that takes into account the hours of play. The proposed recommender system improves the results of other techniques presented in the state of the art.
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