Collaborative filtering based on user's hidden preference model -extraction user's preference from user's rating

摘要

This paper proposes a novel method in collaborative filtering, which helps users in getting contents and items. The effectiveness of collaborative filtering can be assessed by its accuracy of prediction, and the accuracy of prediction depends on the way to seek similar users in preference. Previous works seek these users by the similarity between the users' rating. But our method measures the similarity by the users' preference. To extract these users' preference, we propose the weighting method for item and the introduction of users' hidden preference model. Besides these, we define the formula to predict users' rating. Through the experiments, we can confirm the effectiveness of our method in the accuracy of prediction.