Shang Ming-Sheng and Zhang Zi-Ke 2009 Chinese Phys. Lett. 26 118903 doi:10.1088/0256-307X/26/11/118903
Shang Ming-Sheng1 and Zhang Zi-Ke2
Show affiliationsRecently, 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.
Issue 11 (November 2009)
Received 26 August 2009
Shang Ming-Sheng and Zhang Zi-Ke 2009 Chinese Phys. Lett. 26 118903
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