A New Hybrid Popular Model for Personalized Tag Recommendation
Jing Wang, Nianlong Luo · Journal of Computers · 2015
Tagging systems have been playing an important role in many websites during the web2.0age.Users use a social tagging system to effectively mark web resources with personalized tags, which can help them organize and share their items easily.In this work, we put forward a new model IBHP to recommend personalized tags for users.We evaluate our model on a real-world dataset collected on Delicious 1 .Data tests show that our model can get better performance than currently widely used popularity-based methods, which also use the same available information: ternary relations.