Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10140569 | Physica A: Statistical Mechanics and its Applications | 2019 | 9 Pages |
Abstract
Navigation on graphs is the problem how an agent walking on the graph can get from a source to a target with limited information about the graph. The information and the way to exploit it can vary. In this paper, we study navigation on temporal networks-networks where we have explicit information about the time of the interaction, not only who interacts with whom. We contrast a type of greedy navigation - where agents follow paths that would have worked well in the past - with two strategies that do not exploit the additional information. We test these on empirical temporal network data sets. The greedy navigation finds the targets faster and more reliably than the reference strategies, meaning that there are correlations in the real temporal networks that can be exploited. We find that both topological and temporal structures affect the navigation.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Sang Hoon Lee, Petter Holme,