An Efficient Search Strategy for Service Provider Selection in Complex Social Networks

Yu Xu, Jianxun Liu, Mingdong Tang, Buqing Cao, Xiaoqing Frank Liu
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引用次数: 6

Abstract

The trustworthiness of service providers plays an important role when a consumer selects a service. This paper studies the problem of how to efficiently search and select trustworthy service providers for users in social networks consisting of service providers and consumers. A trust value between two participants can be derived by existing methods from the optimal trust path between them in a social network. When more than one trust factors are taken into consideration, the exact optimal trust path selection algorithm is NP-complete. Although several heuristic algorithms have been proposed to find approximate solutions, their time complexities are still too high to be acceptable in practice, especially when they are used in very large scale social networks. Focusing on reducing trust path searching time, this paper proposes an efficient preprocessing-based search strategy. It exploits structural properties of the social networks and builds an advanced data structure from preprocessing, which can be used to simplify and accelerate the trust path searching. Experimental results show our strategy is very efficient and nearly achieves a constant time complexity. The computed trustworthiness based on our method has excellent performance close to that of the best existing heuristic algorithm.
复杂社会网络中服务提供者选择的有效搜索策略
当消费者选择服务时,服务提供者的可信度起着重要的作用。本文研究了在由服务提供者和消费者组成的社交网络中,如何为用户高效地搜索和选择值得信赖的服务提供者问题。现有的方法可以从社会网络中参与者之间的最优信任路径中得到参与者之间的信任值。当考虑多个信任因素时,精确的最优信任路径选择算法是np完全的。虽然已经提出了几种启发式算法来寻找近似解,但它们的时间复杂度仍然太高,无法在实践中接受,特别是当它们用于非常大规模的社交网络时。针对减少信任路径搜索时间的问题,提出了一种基于预处理的高效搜索策略。该算法利用社会网络的结构特性,通过预处理构建高级数据结构,简化和加速信任路径搜索。实验结果表明,该策略非常有效,几乎达到了恒定的时间复杂度。基于该方法计算的可信度具有接近现有最佳启发式算法的优异性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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