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 et de médecine
- Department
- Département de Physique
- Language
-
- English
- Classification
- Physics
- License
- License undefined
- Identifiers
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- RERO DOC 17079
- DOI 10.1088/0256-307x/26/11/118903
- Persistent URL
- https://folia.unifr.ch/unifr/documents/301467
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