Effective Personalized Recommendation in Collaborative Tagging Systems

2009/07/19 by Zi‐Ke Zhang, Tao Zhou, Zhang, Zi-Ke +1
Computer Science · #Caching and Content Delivery #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Peer-to-Peer Network Technologies #Recommender Systems and Techniques

paper · pdf · doi:10.48550/arxiv.0907.3315

openalex publication_date 2009/07/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Recently, collaborative tagging systems have attracted more and more attention and have been widely applied in web systems. Tags provide highly abstracted information about personal preferences and item content, and are therefore potential to help in improving better personalized recommendations. In this paper, we propose a tag-based recommendation algorithm considering the personal vocabulary and evaluate it in a real-world dataset: Del.icio.us. Experimental results demonstrate that the usage of tag information can significantly improve the accuracy of personalized recommendations.

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