Abstract
Though various contents are provided through the internet recently, it is not easy to collect favorite contents among huge amounts of contents in terms of user's preference. In this paper, we focus on the collaborative filtering algorithm in the recommender system. We propose a fuzzy modeling approach for collaborative filtering. In our approach, valid simplified fuzzy model is constructed through optimization of MAE(Mean Absolute Error) and ROC(Receiver Operating Characteristic). The model decides the weights of similarity from the value of correlation and the number of used evaluation items. Through numerical experiments using MovieLens data, the approach is found to be promised for improvement of filtering model accuracy.
