Chin. Phys. Lett.  2009, Vol. 26 Issue (11): 118903    DOI: 10.1088/0256-307X/26/11/118903
CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY |
Diffusion-Based Recommendation in Collaborative Tagging Systems
SHANG Ming-Sheng1, ZHANG Zi-Ke2
1School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 6100542Department of Physics, University of Fribourg, CH-1700 Fribourg, Switzerland
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SHANG Ming-Sheng, ZHANG Zi-Ke 2009 Chin. Phys. Lett. 26 118903
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Abstract 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.
Keywords: 89.75.-k      89.20.-a      89.20.Ff     
Received: 26 August 2009      Published: 30 October 2009
PACS:  89.75.-k (Complex systems)  
  89.20.-a (Interdisciplinary applications of physics)  
  89.20.Ff (Computer science and technology)  
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https://cpl.iphy.ac.cn/10.1088/0256-307X/26/11/118903       OR      https://cpl.iphy.ac.cn/Y2009/V26/I11/118903
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SHANG Ming-Sheng
ZHANG Zi-Ke
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