Suppr超能文献

基于链路预测评估链路在维持网络连通性方面的重要性。

Evaluating link significance in maintaining network connectivity based on link prediction.

作者信息

Qi Mingze, Tan Suoyi, Deng Hongzhong, Wu Jun

机构信息

College of Systems Engineering, National University of Defense Technology, Changsha, Hunan 410073, People's Republic of China.

International Academic Center of Complex Systems, Beijing Normal University, Zhuhai, Guangdong 519087, People's Republic of China.

出版信息

Chaos. 2019 Aug;29(8):083120. doi: 10.1063/1.5091608.

Abstract

Evaluating the significance of nodes or links has always been an important issue in complex networks, and the definition of significance varies with different perspectives. The significance of nodes or links in maintaining the network connectivity is widely discussed due to its application in targeted attacks and immunization. In this paper, inspired by the weak tie phenomenon, we define the links' significance by the dissimilarity of their endpoints. Some link prediction algorithms are introduced to define the dissimilarity of nodes based solely on the network topology. Experiments in synthetic and real networks demonstrate that the method is especially effective in the networks with higher clustering coefficients.

摘要

评估节点或链接的重要性一直是复杂网络中的一个重要问题,并且重要性的定义因不同视角而异。由于其在靶向攻击和免疫中的应用,节点或链接在维持网络连通性方面的重要性受到了广泛讨论。在本文中,受弱联系现象的启发,我们通过链接端点的差异来定义链接的重要性。引入了一些链接预测算法,仅基于网络拓扑来定义节点的差异。在合成网络和真实网络中的实验表明,该方法在具有较高聚类系数的网络中特别有效。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验