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A new weighting method in network-based recommendation

Author

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  • Jia, Chun-Xiao
  • Liu, Run-Ran
  • Sun, Duo
  • Wang, Bing-Hong

Abstract

In this paper, we propose a influence-based approach to investigate network-based recommendation systems. Different from the previous mass diffusion approach, we give a new expression of initial resource distribution and take into account the influence of resources associated with the receiver nodes. According to ranking score and two measures about the degree of personalization, we demonstrate that our method can outperform the previous methods greatly. It’s found that there exists an optimal initial resource distribution that leads to the best algorithmic accuracy and personalization strength. The optimal initial resource distribution indicates that we should increase the initial resource located on popular objects, rather than decrease them.

Suggested Citation

  • Jia, Chun-Xiao & Liu, Run-Ran & Sun, Duo & Wang, Bing-Hong, 2008. "A new weighting method in network-based recommendation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5887-5891.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:23:p:5887-5891
    DOI: 10.1016/j.physa.2008.06.046
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    Citations

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    Cited by:

    1. Chen, Ling-Jiao & Zhang, Zi-Ke & Liu, Jin-Hu & Gao, Jian & Zhou, Tao, 2017. "A vertex similarity index for better personalized recommendation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 607-615.
    2. Wen, Yuan & Liu, Yun & Zhang, Zhen-Jiang & Xiong, Fei & Cao, Wei, 2014. "Compare two community-based personalized information recommendation algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 199-209.
    3. Yin, Chun-Xia & Peng, Qin-Ke & Chu, Tao, 2012. "Personal artist recommendation via a listening and trust preference network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(5), pages 1991-1999.
    4. Liu, Chuang & Zhou, Wei-Xing, 2012. "Heterogeneity in initial resource configurations improves a network-based hybrid recommendation algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5704-5711.

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