Diffusion-based recommendation in collaborative tagging systems

Shang, Ming-Sheng; Zhang, Zi-Ke

doi:10.1088/0256-307x/26/11/118903

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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 et de médecine

Department

Département de Physique

Language