HYBRID COLLABORATIVE FILTERING BASED ON RATING AND TAGGING INFORMATION

Recently, social tagging system has become popular in the Internet, which provides an effective way for the users to manage and share their resources. Meanwhile, the tagging information can provide many users' preferences. In this paper, we propose a hybrid collaborative filtering method to promote the recommendation quality derived from the users' rating and tagging information. This algorithm combines collaborative tagging and collaborative rating together to grasp and filter the users' preferences, which can avoid some limitations from collaborative filtering algorithm. In addition, we present the empirical experiments using the real dataset from Movie Lens. The experiment results show that our proposed algorithm can promote the recommendation quality significantly.