Mapping the forms of meaning in small worlds

被引:7
作者
Gaume, Bruno [1 ]
机构
[1] Univ Toulouse 3, Inst Rech Informat Toulouse, F-31062 Toulouse 4, France
关键词
Complex networks - Markov processes - Graph theory;
D O I
10.1002/int.20275
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Prox is a stochastic method to map the local and global structures of real-world complex networks, which are called small worlds. Prox transforms a graph into a Markov chain; the states of which are the nodes of the graph in question. Particles wander from one node to another within the graph by following the graph's edges. It is the dynamics of the particles' trajectories that map the structural properties of the graphs that are studied. Concrete examples are presented in a graph of synonyms to illustrate this approach. (c) 2008 Wiley Periodicals, Inc.
引用
收藏
页码:848 / 862
页数:15
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