Path association rule mining
Databases
2022-10-25 v1
Abstract
Graph association rule mining is a data mining technique used for discovering regularities in graph data. In this study, we propose a novel concept, {\it path association rule mining}, to discover the correlations of path patterns that frequently appear in a given graph. Reachability path patterns (i.e., existence of paths from a vertex to another vertex) are applied in our concept to discover diverse regularities. We show that the problem is NP-hard, and we develop an efficient algorithm in which the anti-monotonic property is used on path patterns. Subsequently, we develop approximation and parallelization techniques to efficiently and scalably discover rules. We use real-life graphs to experimentally verify the effective
Cite
@article{arxiv.2210.13136,
title = {Path association rule mining},
author = {Yuya Sasaki},
journal= {arXiv preprint arXiv:2210.13136},
year = {2022}
}