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An Efficient Trust Propagation Scheme for Predicting Trustworthiness of Service Providers in Service-Oriented Social Networks

机译:预测面向服务的社交网络中服务提供商的可信度的有效信任传播方案

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Perception of trustworthiness of service providers is a fundamental need in service selection. Trust propagation has been used to predict trustworthiness of service providers in service-oriented social networks. However, existing trust propagation methods may suffer from a scalability problem, i.e., their computation time is likely too high to be acceptable in practice, especially when they are applied to very large-scale service-oriented social networks. Moreover, they rarely consider the structural properties of social networks to optimize their performance. This paper proposes an efficient trust propagation scheme for predicting trust in service-oriented social networks. It exploits the specific structural properties of social networks and builds an advanced data structure from preprocessing to improve the efficiency of trust propagation. Our scheme can support multiple trust propagation strategies. Experiments show that our scheme is much more efficient than well-known trust propagation methods in trust prediction, while its trust prediction results are as accurate as theirs in service-oriented social networks.
机译:对服务提供商的可信度的感知是选择服务的基本需求。信任传播已用于预测面向服务的社交网络中服务提供者的信任度。然而,现有的信任传播方法可能遭受可伸缩性问题,即,它们的计算时间可能太长而在实践中不能被接受,尤其是当它们被应用到非常大规模的面向服务的社交网络时。而且,他们很少考虑社交网络的结构属性来优化其性能。本文提出了一种有效的信任传播方案,用于预测面向服务的社交网络中的信任。它利用社交网络的特定结构属性,并从预处理构建高级数据结构,以提高信任传播的效率。我们的方案可以支持多种信任传播策略。实验表明,该方案在信任预测中比众所周知的信任传播方法高效得多,而其信任预测结果与面向服务的社交网络中的结果一样准确。

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