English

Deterministic walks in random networks: an application to thesaurus graphs

Disordered Systems and Neural Networks 2010-06-10 v3 Statistical Mechanics

Abstract

In a landscape composed of N randomly distributed sites in Euclidean space, a walker (``tourist'') goes to the nearest one that has not been visited in the last \tau steps. This procedure leads to trajectories composed of a transient part and a final cyclic attractor of period p. The tourist walk presents universal aspects with respect to \tau and can be done in a wide range of networks that can be viewed as ordinal neighborhood graphs. As an example, we show that graphs defined by thesaurus dictionaries share some of the statistical properties of low dimensional (d=2) Euclidean graphs and are easily distinguished from random graphs. This approach furnishes complementary information to the usual clustering coefficient and mean minimum separation length.

Keywords

Cite

@article{arxiv.cond-mat/0110217,
  title  = {Deterministic walks in random networks: an application to thesaurus graphs},
  author = {O. Kinouchi and A. S. Martinez and G. F. Lima and G. M. Lourenco and S. Risau-Gusman},
  journal= {arXiv preprint arXiv:cond-mat/0110217},
  year   = {2010}
}

Comments

12 pages, 5 figures, revised version submited to Physica A, corrected references to figures

R2 v1 2026-07-22T10:28:31.035Z