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Journal article

Hybrid recommendation algorithm based on two roles of social tags

  • Zhang, Zi-Ke Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China - Department of Physics University of Fribourg, Switzerland
  • Liu, Chuang Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China
    2011
Published in:
  • International Journal of Bifurcation and Chaos. - 2012, vol. 22, no. 07, p. 1250166
Personalized recommendation
social tagging networks
hybrid
English The past few years have witnessed the great success of a new family of paradigms, social tagging networks, which allows users to freely associate social tags to items and efficiently manage them. Thus it provides us a promising way to effectively find useful and interesting information. In this paper, we consider two typical roles of social tags: (i) an accessorial tool helping users organize items; (ii) a bridge that connects users and items. We then propose a hybrid algorithm to integrate the two different roles to obtain better recommendation performance. Experimental results on a real-world data set, Del.icio.us, shows that it can significantly enhance both the algorithmic accuracy and diversity.
Faculty
Faculté des sciences et de médecine
Department
Département de Physique
Language
  • English
Classification
Physics
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/302702
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