Personalized Web Service Recommendation Based on Heterogeneous Social Network
YANG Jie1, ZHU Xian-jun2, ZHOU Xian-zhong3, LIU Yi1
1. Department of Information Management, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China;
2. School of Software Engineering, Jinling Institute of Technology, Nanjing, Jiangsu 211169, China;
3. Department of Control and System Engineering, Nanjing, Jiangsu 210093, China
Abstract:To ease cold start and data sparsity problems in web service recommendation, and satisfy user’s personalized requirements, we propose a web service recommendation framework and algorithms based on heterogeneous social network.Web service provider, as an element in the network, could provide more real information to help relieve cold start.Based on the proposed recommendation framework, we design CTV (Computing Trust Value) algorithm to predict trust value of user to candidate service and RQ (Recommend Queue) algorithm to recommend services.At last, we conduct a series of experiments based on real data set.The results indicate that the proposed method outperforms the existing methods at the metrics of MAE, RMSE for predictive accuracy, MAP, NDCG for recommendation accuracy, and filling ratio and coverage ratio, and it is helpful to improve personalized recommendation performance.
杨洁, 朱咸军, 周献中, 柳毅. 基于混杂社会网络的个性化Web服务推荐方法[J]. 电子学报, 2020, 48(2): 341-349.
YANG Jie, ZHU Xian-jun, ZHOU Xian-zhong, LIU Yi. Personalized Web Service Recommendation Based on Heterogeneous Social Network. Acta Electronica Sinica, 2020, 48(2): 341-349.
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