A TrueSkill approach for movies recommendation

In this work a probabilistic approach based on TrueSkill for Preference Elicitation is presented. This approach allow us to tackle the "cold start" problem because relies on a content based recommendation system. In addition, it is valuable for handling high uncertainty due there is no dependency on the number of products and users. The only dependency is on ratings given by users on products. The proposal is highly scalable due to user preferences get richer as they are added.