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Mapping the forms of meaning in small worlds
Author(s) -
Gaume Bruno
Publication year - 2008
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20275
Subject(s) - graph , markov chain , computer science , theoretical computer science , graph property , mathematics , voltage graph , line graph , machine learning
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. © 2008 Wiley Periodicals, Inc.