空间活跃度网络模型构建与特性研究

doi:10.11772/j.issn.1001-9081.2016.06.1502

计算机应用 ›› 2016, Vol. 36 ›› Issue (6): 1502-1505.DOI: 10.11772/j.issn.1001-9081.2016.06.1502

空间活跃度网络模型构建与特性研究

陈超, 陈趣, 韩定定

上海市多维度信息处理重点实验室(华东师范大学), 上海 200241

收稿日期:2015-11-02 修回日期:2015-12-28 出版日期:2016-06-10 发布日期:2016-06-08
通讯作者: 韩定定
作者简介:陈超(1990-),男,浙江嘉兴人,硕士研究生,主要研究方向:复杂网络、智能化信息处理;陈趣(1988-),女,浙江舟山人,博士研究生,主要研究方向:复杂网络、智能化信息处理;韩定定(1968-),女,上海人,教授,博士,主要研究方向:信息通信、信息处理、复杂系统、复杂网络、电路设计与测试。

Modeling and characteristic research for spatial activity network

CHEN Chao, CHEN Qu, HAN Dingding

Shanghai Key Laboratory of Multidimensional Information Processing(East China Normal University), Shanghai 200241, China

Received:2015-11-02 Revised:2015-12-28 Online:2016-06-10 Published:2016-06-08

摘要/Abstract

摘要： 基于现实网络拓扑的时变特征,利用Twitter数据集构建了在线社交网络,分析发现网络中用户的活跃度分布独立于时间尺度,并且网络的度分布与边长分布均具有异质性。结合该网络的特点,提出了一种空间活跃度网络模型。模型中网络的拓扑变化受节点活跃度和偏好连边概率影响,通过统计特性分析验证了机制的准确性。为了研究时变网络的动力学过程,在空间活跃度网络中进行了随机游走,得到节点活跃度越大、平均首达时间越短的结论。最后在基于最短路径的搜索策略下研究了偏好连边幂指数与平均搜索时间的关系,发现在空间活跃度网络中使搜索效率最高的幂指数在2左右。该活跃度网络模型可应用于时变网络。

关键词: 时变网络, 活跃度驱动, 空间特性, 随机游走, 最优搜索

Abstract: Based on the characteristics of time-varying for the topology of real networks, an online social network was constructed by Twitter data set. Some results were found that the activity distribution of users was virtually independent of the time scale and degree distribution was heterogeneous as well as the side length distribution through analysis. Combined with the characteristics of the network, a spatial activity network model was proposed. The network topology was affected by the activity of nodes and the preferential attachment probability, the accuracy of the mechanism was proved through the analysis of the statistical characteristics. In order to study the dynamic process in time-varying network, a random walk process was carried out in the spatial activity network, the conclusion was obtained that the Mean First-Passage Time (MFPT) was shorter when the node was more active. Finally, the relationship between the preferential attachment power exponent and the average search time was discussed, and it was found that the power exponent with the highest search efficiency was 2 in spatial activity network. The proposed activity network model can be applied to time-varying network.

Key words: time-varying network, activity driven, spatial property, random walk, optimal search

中图分类号:

TP393.02

陈超, 陈趣, 韩定定. 空间活跃度网络模型构建与特性研究[J]. 计算机应用, 2016, 36(6): 1502-1505.

CHEN Chao, CHEN Qu, HAN Dingding. Modeling and characteristic research for spatial activity network[J]. Journal of Computer Applications, 2016, 36(6): 1502-1505.

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空间活跃度网络模型构建与特性研究

Modeling and characteristic research for spatial activity network

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