This article describes a framework that captures collaborative tagging systems, and derives from it an overview of user tasks that qualify for personalization in such a system. Major research areas have focused on some of these tasks, but we identify many more opportunities. We propose a collaborative model that combines collaborative filtering and information retrieval techniques in order to assists the user to achieve these tasks. Based only on the user’s tags, this personalization model assumes that a user’s tags identify this user’s taste. Because many users do not only tag the content that matches their taste, we propose an evaluating experiment that shows if rating information can be used to adjust the users’ taste profiles. This experiment is one of the steps to advance to a completely personalized model, integrating user preference, content annotations and people relations.
Content
Author and article information
Contributors
Maarten Clements
Conference
Publication date:
August
2007
Publication date
(Print):
August
2007
Pages: 1-6
Affiliations
[0001]Faculty of Electrical Engineering, Mathematics and Computer Science
Delft University of Technology
The Netherlands