Graph-theory in network analysis." Social Networks 5 (2): 235-244. Bayse, W.A. and C.G. MorrisGraph theory in network analysis - Barnes () Citation Context ...the historical and contemporary processessinvolved in the generation and adaptation of knowledge and technology of trees and tree...
图论〔Graph Theory〕是数学的一个分支。它以图为研究对象。图论中的图是由若干给定的点及连接两点的线所构成的图形,这种图形通常用来描述某些事物之间的某种特定关系,用点代表事物,用连接两点的线表示相应两个事物间具有这种关系。 图论的基本研究对象——图 图(Graph)是表示物件与物件之间的关系的数学对象,是图论...
Renormalization of Tensor Network States - KITPC重整化的网络状态-张量理论物理所 Social Network Theory社会网络理论 A Theory and Experiments of Learning in Social Networks(社交网络中的学习理论与实验) Building a Network Theory of Social Capital - :建立一个网络的社会资本理论- 网络优化理论和技术--学员用...
Graph theory is also widely used in sociology as a way, for example, to measure actors' prestige or to explore rumor spreading, notably through the use of social network analysis software. Under the umbrella of social networks are many different types of graphs. Acquaintanceship and friendship gr...
《Network Science》书中,作者Albert-Laszlo Barabasi在介绍哥尼斯堡问题的最后,用了这样一句话对当时人们的探索行为做了总结: The people of Königsberg gave up their fruitless search. ——哥尼斯堡的人们最终放弃了他们徒劳无功的尝试 可以看出,能否找到一条满足要求的道路其实并不依靠人们的聪明才智,这是图结构...
脑网络的研究需要用到graph theory。简单来说,通常认知神经科学的研究对象是涉及某个认知任务的单个或者多个脑区,但是不考虑脑区之间的联系(即功能连接或者结构连接),脑网络研究或者连接组的研究则会考虑到多个脑区间的协同合作。 关于图论或者拓扑学是具体怎么和大脑的研究结合的,题主可以关注几个相关领域的大牛写的...
Models are extremely important in modern network theory. It can be argued that the discovery of models for very large networks with a mixture of randomness and order lies at the heart of the transition from conventional graph theory to the modern science of networks. Here we describe three prot...
(intv,intparent){// the lowest back edge discovery time of `v` is// set to the discovery time of `v` initallyback[v]=time_in[v]=++time_spent;for(inti=0;i<g[v].size();i+=1){intnext=g[v][i];if(next==parent){continue;}if(time_in[next]==-1){dfs(next,v);// if ...
2001到2010年间,因为Social Networks的兴起,曾经有一段时间有很多学者热衷于研究Graph Theory,以及Graph Theory在Semi-supervised Learning中的应用,在Community Detection中的应用等等。 那么,在深度学习席卷的今天,这些研究又如何和深度学习衔接上呢?在CVPR 2017的一个讲座中(http://geometricdeeplearning.com),来自瑞士...
而如果你看过谱聚类(详细可看图卷积神经网络(Graph Convolutional Network, GCN)),当M等于标准化的laplace矩阵L时,即 \displaystyle L=I-\frac{1}{d} A ,你会知道如果设 \displaystyle x\in \{0,1\}^{V},(用1表示A类结点,用0表示B类结点),那么这A,B两类结点把他切割开,于是 \displaystyle \mathbf{...