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http://dx.doi.org/10.3745/JIPS.01.0071

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)
Publication Information
Journal of Information Processing Systems / v.17, no.2, 2021 , pp. 426-439 More about this Journal
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
Cold Boot; Hybrid Social Networks; Personalized Recommendation; Multi-Objective Immune Optimization; Service Providers; Web Service Recommendation;
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