Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Personalized Web Service Recommendation Method Based on Hybrid Social Network and Multi-Objective Immune Optimization

  • Cao, Huashan (Dept. of Dean's Office, Hunan Mass Media Vocational and Technical College)
  • Received : 2020.09.04
  • Accepted : 2020.11.11
  • Published : 2021.04.30
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Abstract

To alleviate the cold-start problem and data sparsity in web service recommendation and meet the personalized needs of users, this paper proposes a personalized web service recommendation method based on a hybrid social network and multi-objective immune optimization. The network adds the element of the service provider, which can provide more real information and help alleviate the cold-start problem. Then, according to the proposed service recommendation framework, multi-objective immune optimization is used to fuse multiple attributes and provide personalized web services for users without adjusting any weight coefficients. Experiments were conducted on real data sets, and the results show that the proposed method has high accuracy and a low recall rate, which is helpful to improving personalized recommendation.

Keywords

Acknowledgement

This work was supported by 2017 Hunan Natural Science Fund Project (No. 2017JJ5008).

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