Revisiting Interval Graphs for Network Science

TL;DR

This paper explores the potential of interval graphs to model multi-relational networks in network science, revisiting a classical concept to address modern complex systems.

Contribution

It reexamines interval graphs within the context of network science, highlighting their relevance for multi-relational network modeling.

Findings

Interval graphs can represent multi-relational network structures.

Revisiting classical graph models offers new insights for network science.

Interval graphs may facilitate analysis of complex, multi-dimensional systems.

Abstract

The vertices of an interval graph represent intervals over a real line where overlapping intervals denote that their corresponding vertices are adjacent. This implies that the vertices are measurable by a metric and there exists a linear structure in the system. The generalization is an embedding of a graph onto a multi-dimensional Euclidean space and it was used by scientists to study the multi-relational complexity of ecology. However the research went out of fashion in the 1980s and was not revisited when Network Science recently expressed interests with multi-relational networks known as multiplexes. This paper studies interval graphs from the perspective of Network Science.