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局部拓扑信息耦合促进网络演化

刘树新 季新生 刘彩霞 汤红波 巩小锐

刘树新, 季新生, 刘彩霞, 汤红波, 巩小锐. 局部拓扑信息耦合促进网络演化[J]. 电子与信息学报, 2016, 38(9): 2180-2187. doi: 10.11999/JEIT151338
引用本文: 刘树新, 季新生, 刘彩霞, 汤红波, 巩小锐. 局部拓扑信息耦合促进网络演化[J]. 电子与信息学报, 2016, 38(9): 2180-2187. doi: 10.11999/JEIT151338
LIU Shuxin, JI Xinsheng, LIU Caixia, TANG Hongbo, GONG Xiaorui. Information Coupling of Local Topology Promoting the Network Evolution[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2180-2187. doi: 10.11999/JEIT151338
Citation: LIU Shuxin, JI Xinsheng, LIU Caixia, TANG Hongbo, GONG Xiaorui. Information Coupling of Local Topology Promoting the Network Evolution[J]. Journal of Electronics & Information Technology, 2016, 38(9): 2180-2187. doi: 10.11999/JEIT151338

局部拓扑信息耦合促进网络演化

doi: 10.11999/JEIT151338
基金项目: 

国家自然科学基金创新研究群体项目(61521003),国家高技术研究发展计划(2014AA01A701)

Information Coupling of Local Topology Promoting the Network Evolution

Funds: 

The Foundation for Innovative Research Groups of the National Natural Science Foundation of China (61521003), The National High Technology Research and Development Program of China (2014AA01A701)

  • 摘要: 为了研究局部拓扑信息耦合对网络演化的促进作用,该文提出一种局部拓扑加权方法,用于表征节点间联系的紧密性及拓扑信息的耦合程度,并从演化模型的宏观统计和实际网络数据测试两方面验证了局部拓扑信息耦合促进网络演化的有效性。首先将该加权方法应用于BA模型,提出TwBA模型及局域世界模型TwLW。仿真实验表明,TwBA的度分布随连边数目的增多,迅速从指数分布转变为幂律分布,验证了现实网络加速增长产生幂律分布的现象,并基于此提出一种加速演化的TwBA模型,其在不同的加速率下呈现出幂律分布;而TwLW则展现了从广延指数分布到幂律分布变化的形式。然后将加权方法拓展到链路预测方法,提出3个加权相似性指标。实际网络数据测试表明,该方法能够大幅度地提高基本算法的预测精度,部分甚至高于全局性指标。
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出版历程
  • 收稿日期:  2015-11-26
  • 修回日期:  2016-04-07
  • 刊出日期:  2016-09-19

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