利用节点传播熵识别超网络重要节点  

Important Node Recognition in Hypernetworks Based on Node Propagation Entropy

作　　者：吴英晗 田阔 李明达 胡枫[1,2,3] WU Yinghan;TIAN Kuo;LI Mingda;HU Feng(College of Computer,Qinghai Normal University,Qinghai 810008,China;The State Key Laboratory of Tibetan Intelligent Information Processing and Application,Qinghai 810008,China;Academy of Plateau Science and Sustainability,Qinghai 810008,China)

机构地区：[1]青海师范大学计算机学院,青海810008 [2]藏语智能信息处理及应用国家重点实验室,青海810008 [3]高原科学与可持续发展研究院,青海810008

出　　处：《计算机工程与应用》2023年第19期66-74,共9页Computer Engineering and Applications

基　　金：国家自然科学基金(61663041);青海省“昆仑英才”行动计划(青人才字[2022]1号);青海省基础研究计划(2023-ZJ-916M)。

摘　　要：超网络中识别重要节点是一项基础且具有挑战性的重要课题,相关研究对进一步分析网络拓扑结构和功能特性具有广泛的应用价值。为了突破已有的重要节点识别方法评估的局限性,利用超图及信息熵理论,提出一种基于节点传播熵的超网络重要节点识别方法。该方法兼顾节点的局部和全局拓扑信息,利用节点聚集系数和邻居数目表征节点信息的局部传播影响,通过节点间最短路径和K壳中心性反映节点信息的全局传播影响,充分考虑节点自身及其邻域节点的影响,最终利用节点传播熵来表征节点在网络中的重要性。并通过单调性、鲁棒性以及SIR传播模型评价标准,在六个来自不同领域的真实网络上与其他方法进行比较,实验结果表明,该方法能够准确有效地识别网络中的重要节点。It is a basic and challenging task to identify important nodes in hypernetworks,and the related research is of great value for further analysis of network topology and functional characteristics.In order to break through the limitations of the existing important node recognition methods,an important node recognition method based on node propagation entropy is proposed by using hypergraph and information entropy theory.This method takes into account both local and global topology information of nodes,uses the node clustering coefficient and the number of neighbors to represent the local propagation influence of node information,the global influence of the node information is reflected by the shortest path between nodes and K-shell centrality,and fully considers the influence of nodes and their neighbors,the importance of nodes in the network is represented by the size of node propagation entropy finally.Using monotonicity,robustness and SIR propagation model evaluation criteria,compared with other methods on six real networks from different fields,experi-mental results show that the proposed method can identify the important nodes in the hypernetwork accurately and effectively.

关 键 词：超图 超网络 重要节点 节点传播熵 

分 类 号：TP301.5[自动化与计算机技术—计算机系统结构]