Personalized Web Service Recommendation Method Based on Hybrid Social Network and Multi-Objective Immune Optimization
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초록
To alleviate the cold-start problem and data sparsity in web service recommendation and meet the personalizedneeds of users, this paper proposes a personalized web service recommendation method based on a hybridsocial 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 theproposed service recommendation framework, multi-objective immune optimization is used to fuse multipleattributes 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 accuracyand a low recall rate, which is helpful to improving personalized recommendation.
Abstract
To alleviate the cold-start problem and data sparsity in web service recommendation and meet the personalizedneeds of users, this paper proposes a personalized web service recommendation method based on a hybridsocial 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 theproposed service recommendation framework, multi-objective immune optimization is used to fuse multipleattributes 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 accuracyand a low recall rate, which is helpful to improving personalized recommendation.
참고문헌 (15)
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