摘要：

在社交网络信任度研究领域中,多数模型或算法仅适用于小规模网络,或在大规模网络中效率低下。为此,综合考虑网络中的节点拓扑结构和用户信任率信息,提出一种针对大规模社交网络的信任度预测算法。将大规模社交网络约简为一个信任图,在该信任图上计算用户间的 信任度。其中,节点的拓扑结构信息可在线下计算。实验结果表明,与典型的信任度预测算法Tidal Trust、SWTrust相比,该算法具有较高的预测精度和计算效率。

关键词: 大规模社交网络, 信任度预测, 拓扑结构, 用户信任率, 信任图

Abstract:

At present,in the research field of social network trust degree prediction,most proposed models or algorithms just are suitable for small-scale network,or have bad efficiency in large-scale network.To solve this problem,considering the node topological structure information and the user trust rate information in the network,a trust degree prediction algorithm for large-scale social network is proposed.The large-scale social network is reduced to a trust graph,and the trust degree between users is calculated on the trust graph.The topological structure information of nodes can be calculated under line.Experimental results show that,compared with the typical trust prediction algorithm Tidal Trust and SWTrust,the proposed algorithm has higher prediction accuracy and computational efficiency.

Key words: large-scale social network, trust degree prediction, topological structure, user trust rate, trust graph

中图分类号: 

• TP393