arXiv Open Access 2022

Path association rule mining

Yuya Sasaki
Lihat Sumber

Abstrak

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

Topik & Kata Kunci

Penulis (1)

Y

Yuya Sasaki

Format Sitasi

Sasaki, Y. (2022). Path association rule mining. https://arxiv.org/abs/2210.13136

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2022
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓