大规模社会网络中信任评估的计算方法研究

Shahriar Etemadi Tajbakhsh, Gaojie Chen, J. Coon
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引用次数: 2

摘要

在本文中,我们考虑了评估社会网络中个体之间信任的问题。之前介绍的三值主观逻辑(3VSL)为衡量社会人际网络中的人际信任提供了一套有用的工具。然而,这种测量所需的操作数量随着网络的规模呈指数增长。此外,没有考虑由共同边引起的连接两个个体的不同路径之间的相关性。在本文中,我们证明了即使考虑到这种相关性,3VSL中的算子仍然可以用来给出信任的下界。我们引入了一个低复杂度的可扩展算法来获得这个下界。给出了数值实验结果,并与3VSL进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On computational approaches to trust evaluation in large-scale social networks
In this paper, we consider the problem of evaluating trust between individuals in social networks. The previously introduced three-valued subjective logic (3VSL) provides a set of useful tools in measuring interpersonal trust in social human networks. However, the number of required operations for such measurements grows exponentially with the size of network. Moreover, the correlations between different paths connecting the two individuals caused by common edges are not considered. In this paper, we show that the operators in 3VSL can still be used to give a lower-bound on trust even if such correlations are taken into account. We introduce a low complexity scalable algorithm to obtain this lower-bound. The numerical experiment results are represented and compared with the 3VSL.
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