Deterministic Graph-Walking Program Mining

TL;DR

This paper introduces a formal framework for mining deterministic graph-walking programs that identify linear long-distance relationships between vertex sets in complex graphs, with algorithms that generate programs of increasing length.

Contribution

It formalizes the concept of connection via graph-walking programs and provides algorithms for mining these programs to reveal relationships in graph data.

Findings

Algorithms successfully mine programs of increasing length

Programs characterize linear long-distance relationships

Framework formalizes connection in graphs

Abstract

Owing to their versatility, graph structures admit representations of intricate relationships between the separate entities comprising the data. We formalise the notion of connection between two vertex sets in terms of edge and vertex features by introducing graph-walking programs. We give two algorithms for mining of deterministic graph-walking programs that yield programs in the order of increasing length. These programs characterise linear long-distance relationships between the given two vertex sets in the context of the whole graph.