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.Comment: 12 pages, 5 figures, revised version submited to Physica A, corrected
references to figure