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A link prediction algorithm based on support vector machine

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  • Zhou, Yinzuo
  • Chen, Weilun
  • Zou, Huangrong

Abstract

The path-based similarity index algorithm has proven effective in link prediction, with the Local Path (LP) similarity index leveraging second-order path information to enhance accuracy significantly. However, few machine learning-based link prediction algorithms fully utilize higher-order path information beyond the second order. Addressing this gap, this paper proposes a novel link prediction algorithm, termed Link Prediction based on Support Vector Machine, which incorporates the concept of the LP similarity index into feature vector construction, integrating higher-order path information comprehensively. Extensive controlled experiments on four public datasets demonstrate that our algorithm achieves notable performance improvements compared to traditional similarity index-based link prediction algorithms.

Suggested Citation

  • Zhou, Yinzuo & Chen, Weilun & Zou, Huangrong, 2025. "A link prediction algorithm based on support vector machine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 673(C).
    • Handle: RePEc:eee:phsmap:v:673:y:2025:i:c:s0378437125003267
    DOI: 10.1016/j.physa.2025.130674
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    References listed on IDEAS

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    Cited by:

    1. Chen, Weilun & Zou, Huangrong & Zhou, Yinzuo, 2025. "A link prediction algorithm based on convolutional neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 678(C).

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