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Multiangle Social Network Recommendation Algorithms and Similarity Network Evaluation

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  • Jinyu Hu
  • Zhiwei Gao
  • Weisen Pan

Abstract

Multiangle social network recommendation algorithms (MSN) and a new assessment method, called similarity network evaluation (SNE), are both proposed. From the viewpoint of six dimensions, the MSN are classified into six algorithms, including user-based algorithm from resource point (UBR), user-based algorithm from tag point (UBT), resource-based algorithm from tag point (RBT), resource-based algorithm from user point (RBU), tag-based algorithm from resource point (TBR), and tag-based algorithm from user point (TBU). Compared with the traditional recall/precision (RP) method, the SNE is more simple, effective, and visualized. The simulation results show that TBR and UBR are the best algorithms, RBU and TBU are the worst ones, and UBT and RBT are in the medium levels.

Suggested Citation

  • Jinyu Hu & Zhiwei Gao & Weisen Pan, 2013. "Multiangle Social Network Recommendation Algorithms and Similarity Network Evaluation," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-8, July.
    • Handle: RePEc:hin:jnljam:248084
    DOI: 10.1155/2013/248084
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    Cited by:

    1. Gelan Yang & Qin Yang & Huixia Jin, 2021. "A novel trust recommendation model for mobile social network based on user motivation," Electronic Commerce Research, Springer, vol. 21(3), pages 809-830, September.

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