摘要： 针对社区推荐系统研究中,当推荐节点发生信息流交互时缺乏信任可靠性与动态变化性的问题,融合社区发现中的中心节点和信任节点的推荐算法,提出一种随时序演变的受信任的中心节点推荐方法。该方法利用社区划分提取网络中心节点,并对节点增设信任机制,通过节点信任度控制谣言等不良信息的传播。加入反馈机制对可信节点进行实时更新,以提高信息传播的安全度,从而得到具有信任值动态反馈特性的中心节点选择策略。实验结果表明,与传统可信边社区划分策略相比,该策略能有效减少谣言等不良信息的传播,增强信息流传递可靠性。

关键词: 社区发现, 信任关系, 中心节点, 信息流, 推荐方法

Abstract: Aiming at the problem that the recommended node lacks trust reliability and dynamic changes during information interaction in the study of community recommendation system,this paper uses the recommendation algorithm of the central node and trusted node in community detection and puts forward a central node recommendation method which makes evolution by sequence and is trusted.This method uses community division to extract network center node,establishes trust mechanism for nodes,and uses the node trust to control the spread of bad information.A feedback mechanism is added to update the trusted node and improve the safety of information dissemination,thus obtaining the central node selection strategy with the characteristic of dynamic trust value feedbock.Experimental results show that,compared with the traditional trusted edge community division strategy,this strategy can avoid more rumor spreading and improve the reliability of information flow transmission.

Key words: community detection, trust relationship, central node, information flow, recommendation method

中图分类号: 

• TP393