Collaborative tagging in recommender systems

This paper proposes a collaborative filtering method with user-created tags focusing on changes of web content and internet services. Collaborative tagging is employed as an approach in order to grasp and filter users' preferences for items. In addition, we explore several advantages of collaborative tagging for future searching and information sharing which is used for automatic analysis of user preference and recommendation. We present empirical experiments using real dataset from del.icio.us to demonstrate our algorithm and evaluate performance compared with existing works.