基于零模型的含时网络模体识别方法  

Temporal network motif discovery method based on null model

作　　者：胡博仁 裴忠民 罗章凯 丁杰 HU Boren;PEI Zhongmin;LUO Zhangkai;DING Jie(Key Laboratory of Complex Electronic System Simulation(Space Engineering University),Beijing 101416,China;Department of Electronics and Optical Engineering,Space Engineering University,Beijing 101416,China)

机构地区：[1]复杂电子系统仿真重点实验室(航天工程大学),北京101416 [2]航天工程大学电子与光学工程系,北京101416

出　　处：《计算机应用》2023年第8期2505-2510,共6页journal of Computer Applications

基　　金：复杂电子系统仿真重点实验室资助项目(DXZT-JC-ZZ-2020-001)。

摘　　要：在带有时间属性的含时网络中,常规的基于频繁子图统计的网络模体识别方法容易受网络规模与结构差异的影响。而与实证网络具有相同规模和某些相同性质的零模型网络能为实证网络的特性挖掘提供了准确的基准,于是提出一种基于零模型的含时网络模体识别方法,用两种网络子图特征比较后的相对值来识别含时网络中的具有显著结构意义的子图。同时,为确定零模型网络何时达到稳定,采用成功置乱次数方法来改进基于时间置乱或时间随机化的含时网络零模型构造方法。在实验阶段,对包含卫星和地面站的46节点全球定位系统(GPS)星座进行仿真实验,确定了零模型网络子图特征稳定时的成功置乱次数;构造10个零模型网络与卫星网络比较,发现反映节点连接具有连续性特点的子图的出现次数仅为最高频子图的1/34,却是卫星网络中最重要的模体。实验结果表明,以零模型为参照的含时网络模体识别方法能更准确地识别出反映网络结构特性和动态变化过程的模体。In temporal networks with time attributes,conventional network motif discovery methods based on frequent subgraph statistics are easily affected by the differences in network size and structure.And an accurate benchmark for characteristic mining of empirical network can be provided by the null model network with same scale and some properties of the empirical network.Therefore,a temporal network motif discovery method based on null model was proposed to use relative values after comparing the features of the two network subgraphs to identify the subgraphs with significant structural meaning in temporal networks.At the same time,in order to determine when null model network reached stability,the method of successful scrambling times was adopted to improve the temporal network's null model construction methods based on time scrambling or time randomization.In experiment stage,simulations were conducted on 46-node Global Positioning System(GPS) constellation containing satellites and ground stations,the number of successful scrambles times when the subgraph features of null model network reached stability was determined.Ten null model networks were constructed and compared with the satellite network.It was found that the number of occurrences of subgraph reflecting the continuity characteristics of node connection is only 1/34 of that of the subgraph with the highest frequency,but the former subgraph is the most important motif in the satellite network.Experimental results show that the temporal network's motif discovery method with null model as reference can identify motifs that reflects network structural characteristics and dynamic change process more accurately.

关 键 词：含时网络 模体识别 零模型 成功置乱次数 卫星网络 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]