面向服务的云计算中基于信任的推荐系统

Dehua Kong, Yuqing Zhai
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引用次数: 13

摘要

随着云服务的数量和类型的不断增加,云服务用户很难对这些云服务进行评估和选择,以满足他们的需求。因此,需要适当的推荐机制来帮助他们在具有相同或相似功能的云服务集中选择最佳服务。本文提出了面向服务的云计算(TRSC)中基于信任的推荐系统。我们首先介绍了基于云服务信任度量云服务的TRSC架构。在TRSC中,信任值是直接信任和推荐信任的结合。计算云服务用户a对云服务C的直接信任是基于a与C的直接交互,计算推荐信任的评估方法是基于云服务用户b与C的交互,其中b是受a信任的用户、与a相关的用户或该领域的权威。实验结果表明,与传统的协同过滤相比,该方法可以获得更好的推荐精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trust Based Recommendation System in Service-oriented Cloud Computing
With the increasing number and types of cloud services, it is difficult for cloud service users to evaluate these cloud services and select them to satisfy their requirements. Hence, appropriate recommendation mechanisms are needed to help them to select the optimal services in the set of cloud services with identical or similar functionality. In this paper, we propose a Trust-based Recommendation System in service-oriented Cloud computing(TRSC). We first present the architecture of TRSC which measures cloud services based on the trust of them. In TRSC, the trust value is the combination of direct trust and recommendation trust. Direct trust of a cloud service user A on a cloud service C is computed basing on the direct interaction of A with C. And the evaluation method for calculating recommendation trust is based on the interaction of cloud service users Bs with C where Bs are users who are trusted by A, correlative with A or authorities of the field. The experimental results showed that the proposed approach can get a better recommendation accuracy than traditional collaborative filtering.
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