Volume 11 Number 2 (Mar. 2016)
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JCP 2016 Vol.11(2): 116-123 ISSN: 1796-203X
doi: 10.17706/jcp.11.2.116-123

A New Hybrid Popular Model for Personalized Tag Recommendation

Jing Wang, Nianlong Luo
Information Technology Center, Tsinghua University, Beijing, 100084, China.
Abstract—Tagging systems have been playing an important role in many websites during the web2.0 age. 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 Delicious1. 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.

Index Terms—Hybrid popular, recommender, tagging system, collaborative filtering.

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Cite: Jing Wang, Nianlong Luo, "A New Hybrid Popular Model for Personalized Tag Recommendation," Journal of Computers vol. 11, no. 2, pp. 116-123, 2016.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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