A Probabilistic Ranking Approach for Tag Recommendation
ECML PKDD Discovery Challenge 2009 (DC09), 497, page 143--155. Bled, Slovenia, CEUR Workshop Proceedings, (September 2009)Abstract
Social Tagging is a typical Web 2.0 application for users to share knowledge and organize the massive web resources. Choosing appropriate words as tags might be time consuming for users, thus a tag recommendation system is needed for accelerating this procedure. In this paper we formulate tag recommendation as a probabilistic ranking process, especially we propose a hybrid probabilistic approach which combines language model and statistical machine translation model. Experimental results validate the effectiveness of our method.
