Journal article

Diffusion-based recommendation in collaborative tagging systems

  • Shang, Ming-Sheng School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
  • Zhang, Zi-Ke Department of Physics, University of Fribourg, Switzerland
    2009
Published in:
  • Chinese Physics Letters. - 2009, vol. 26, no. 11, p. 118903
English 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 therefore have the potential to help in improving better personalized recommendations. We propose a diffusion-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.
Faculty
Faculté des sciences
Department
Physique
Language
  • English
Classification
Physics
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/301467
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