《计算机应用研究》|Application Research of Computers

一种有效的动态网络节点影响力模型

Effective model for measuring node influence on temporal network

免费全文下载 (已被下载 次)  
获取PDF全文
作者 韩忠明,毛锐,郑晨烨,赵振东,段大高
机构 北京工商大学 a.计算机与信息工程学院 计算机系;b.食品安全大数据技术北京市重点实验室,北京 100048
统计 摘要被查看 次,已被下载
文章编号 1001-3695(2019)07-009-1960-05
DOI 10.19734/j.issn.1001-3695.2017.11.0847
摘要 网络节点影响力度量对社会网络研究具有重要的价值。静态网络的影响力度量是目前研究的主要问题。实质上,社会网络属于动态网络。静态网络节点影响力度量模型虽然可以对动态网络不同时间点上的快照进行度量,但这种机制很难刻画动态网络节点影响力的变化过程。将动态网络建模为不同时间点网络的叠加快照,然后构建了动态网络边权重衰减和节点影响力衰减机制,基于该机制提出了动态网络节点影响力模型。该模型可应用于加权或无权动态网络节点影响力度量。为了客观地衡量所提模型的性能,在一个模拟网络和三个真实网络上进行了不同实验。实验结果表明所提模型不仅可以较好地刻画动态网络节点影响力的变化过程,还可以准确度量动态网络节点影响力。
关键词 动态网络; 节点影响力; 权重衰减
基金项目 国家自然科学基金资助项目(61170112)
北京市自然科学基金资助项目(4172016)
北京市科技计划课题(Z161100001616004)
北京市教委科研计划面上项目(KM201710011006)
本文URL http://www.arocmag.com/article/01-2019-07-009.html
英文标题 Effective model for measuring node influence on temporal network
作者英文名 Han Zhongming, Mao Rui, Zheng Chenye, Zhao Zhendong, Duan Dagao
机构英文名 a.Dept. of Computer,School of Computer Science & Information Engineering,b.Beijing Key Laboratory of Big Data Technology for Food Safety,Beijing Technology & Business University,Beijing 100048,China
英文摘要 Measuring node influence on network is an important question of online social network analysis. Currently, the main related research focus on influence of static networks. Essentially, social networks are dynamic networks. Although models for measuring node influence on static networks can be used to measure node influence in different snapshots of a temporal network, it is difficult to describe the dynamic process of node influence. This paper viewed a dynamic network as a series of snapshots at different time points. It constructed the mechanisms of edge weight attenuation and node influence attenuation. Based on the attenuation mechanism, this paper proposed a model for measuring node influence on dynamic networks, which could be applied to weighted or unweighted dynamic networks. In order to evaluate the performance of proposed model, it conducted comprehensive experiments on a simulated network and three real networks. The experimental results show that proposed model can not only describe the influence dynamic process for different nodes, but also effectively measure the node influence in dynamic networks.
英文关键词 dynamic network; node influence; weight attenuation
参考文献 查看稿件参考文献
 
收稿日期 2017/11/15
修回日期 2018/3/5
页码 1960-1964
中图分类号 TP393
文献标志码 A