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基于谱分析的复杂网络模式

Patterns in Complex Networks via Spectral Analysis
课程网址: http://videolectures.net/ssspr2010_estrada_pcn/  
主讲教师: Ernesto Estrada
开课单位: 斯特拉斯克莱德大学
开课时间: 2010-09-03
课程语种: 英语
中文简介:
复杂的网络代表着生物学,生态学,社会和技术领域的各种现实世界系统。对此类系统的结构特性的研究对我们对其功能,组织和动力学的理解产生了巨大影响。在这里,我针对复杂网络的结构表征提出了一系列结果。我先分析复杂网络中节点的中心性,然后介绍一种衡量节点在网络中所有子图中的参与度的方法。该方法用于获得将网络分为四个拓扑类别的通用分类。然后,我将开发一种方法来表征网络中节点之间的可通信性。通过在WWW中对网页进行排名来说明该方法,并将其与其他算法(例如PageRank,SALSA等)进行比较。使用可通信性方法,我开发了一种方法来识别网络中的重叠社区。最后,我将这些思想扩展为一般矩阵函数。
课程简介: Complex networks represent a variety of real-world systems in biology, ecology, society and technology. The study of structural properties of such systems has a tremendous impact in our understanding of their function, organisation and dynamics. Here I present a series of results toward the structural characterisation of complex networks. I start by analysing the centrality of nodes in complex networks and we introduce a measure which accounts for the participation of a node in all subgraphs in the network. This method is used to obtain a universal classification of networks into four topological classes. Then, I will develop a method to characterise the communicability between nodes in a network. The method is illustrated by ranking webpages in WWW and it is compared to other algorithms such as PageRank, SALSA, etc. Using the communicability approach I develop a method to identify overlapped communities in networks. I finalise by extending these ideas to account for general matrix functions.
关 键 词: 生物学; 技术领域; 拓扑类别
课程来源: 视频讲座网
最后编审: 2019-09-23:cwx
阅读次数: 41