Service Recommended Trust Algorithm Based on Cloud Model Attributes Weighted Clustering

doi:10.16182/j.issn1004731x.joss.201811031

Abstract

Abstract: In cloud computing, there are cloud services of different qualities. How to choose credible and reliable service has become a key issue when users select services. Aiming at the shortcomings of the existing evaluation methods, a service clustering method based on attributes weighted cloud model is proposed. The users’ evaluation similarity with weighted Pearson correlation coefficient method based on service clustering is calculated. The users’ similarity combined with the index weights of users’ service selection is computed. The nearest neighbors are gotten. The recommendation trust of the services with the recommendation trust algorithm is obtained. Simulation results show that the proposed algorithm can calculate the service recommendation trust more accurately. It meets the demand of users in terms of trust of service and it has the practical significance in improving the quality of selected service.

Key words: cloud model, service clustering, user similarity, recommended trust

CLC Number:

TP391

Wang Jindong, Yu Zhiyong, Zhang Hengwei, Fang Chen. Service Recommended Trust Algorithm Based on Cloud Model Attributes Weighted Clustering[J]. Journal of System Simulation, 2018, 30(11): 4298-4312.

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