2022/10/24 by Yuya Sasaki, Sasaki, Yuya
Computer Science · #Data Mining Algorithms and Applications
paper · pdf · doi:10.48550/arxiv.2210.13136
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