Dynamic Self-Similar kc-Center Network Based on Information
Dissemination

doi:10.1007/s12204-022-2559-6

J Shanghai Jiaotong Univ Sci ›› 2024, Vol. 29 ›› Issue (3): 480-491.doi: 10.1007/s12204-022-2559-6

• Automation & Computer Technologies • Previous Articles Next Articles

Dynamic Self-Similar kc-Center Network Based on Information Dissemination

基于信息传播的动态自相似kc中心网络

WANG Li¹ (李树勋), ZHANG Xuyi² (沈珩云), YAO Yabing³ (刘斌才),HU Yinggang^4*(胡迎港)

(1. Library, Northwest Normal University, Lanzhou 730070, China; 2. Department of Criminal Science and Technology, Henan Police College, Zhengzhou 450046, China; 3. School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China; 4. School of Computer Science and Engineering, Northeastern University, Shenyang 110169, China)
(1. 西北师范大学图书馆，兰州 730070；2. 河南警察学院刑事科学技术系，郑州 450046；3. 兰州理工大学计算机与通信学院，兰州 730050；4. 东北大学计算机科学与工程学院，沈阳 110169)

Accepted:2022-04-03 Online:2024-05-28 Published:2024-05-28

Abstract

Abstract: This study mainly focused on the dynamic self-similar kc-center network as a result of information distribution through social networks. Individual attraction with various preferences was characterized in the model as a result of reciprocal attraction among individuals and human multi-attribute. Additionally, the model incorporated the community network structure and network evolution mechanism, and a dynamic self-similar kc-center network generation model was presented. Compared with the classical scale-free network generation algorithm, the generated network embodied not only the characteristics of the small-world and scale-free, but also the characteristics of dynamic self-similar kc-center network. The experimental results were verified by comparing the real data with the experimental data. The results showed that there are dynamic self-similar kc-center networks and their internal network relationship dynamics in the micro scale, meso scale and global perspective based on information dissemination.

Key words: edge state, evolutionary network, self-similarity, kc-center network

摘要： 本研究主要关注通过社交网络进行信息传播所产生的动态自相似kc中心网络。由于个体间的相互吸引和人类的多属性，该模型描述了具有各种偏好的个体吸引力。此外，该模型还结合了社群网络结构和网络演化机制，提出了动态自相似kc中心网络生成模型。与经典的无标度网络生成算法相比，生成的网络不仅体现了小世界和无标度的特点，还体现了动态自相似kc中心网络的特点。通过将真实数据与实验数据进行对比，验证了实验结果。结果表明：基于信息传播，在微观尺度、中观尺度和全局视角下都存在动态自相似kc中心网络及其内部网络关系动态变化。

关键词: 边状态，演化网络，自相似，kc中心网络

CLC Number:

TP273+.3

WANG Li¹ (李树勋), ZHANG Xuyi² (沈珩云), YAO Yabing³ (刘斌才),HU Yinggang^4*(胡迎港). Dynamic Self-Similar kc-Center Network Based on Information Dissemination[J]. J Shanghai Jiaotong Univ Sci, 2024, 29(3): 480-491.

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Dynamic Self-Similar kc-Center Network Based on Information Dissemination

基于信息传播的动态自相似kc中心网络

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