2013 Volume 22 Issue 2 Pages 95-106
This paper evaluates the performance of Flexible Mixture Model which is one of the probabilistic latent variable models for recommender system. Recently, previous researches showed that the performances of memory-based collaborative filtering methods can be evaluated by Agent-based simulation. Though the effectiveness of methods for recommender system was sometimes clarified by using benchmark data sets, the technique of Agent-based simulation gives us the way to investigate its’ properties from several different viewpoints. It was meaningful to investigate the performance and behavior of memory-based collaborative filtering methods. However, several model-based collaborative filtering methods have been proposed and their effectiveness has been pointed out. It is meaningful to inves- tigate the characteristics and performance of modelbased collaborative filtering. This paper focuses on Flexible Mixture Model and investigate its’ characteristics by Agent-based simulation techniques.
