JOURNAL ARTICLE

Efficient Searching of Subhypergraph Isomorphism in Hypergraph Databases

Abstract

A hypergraph consisting of nodes and hyperedges that connects multiple nodes can model complex relationships among entities effectively. In this work, we study a subhypergraph isomorphism search method that finds all isomorphic subhypergraphs to the query. Existing works of subgraph isomorphism in an ordinary graph try to reduce search space for a query graph to decrease computational costs, since a subgraph isomorphism problem is known to be NP-hard. However, previous methods of finding isomorphic subhypergraphs for hypergraphs do not make much effort for decreasing costs. In this paper, we propose a method that finds subhypergraph isomorphism efficiently. We first select nodes and edges that are likely to match to a query hypergraph, with consideration for characteristics of hyperedges. Then, we verify isomorphism between remaining subgraphs of data hypergraph and a query hypergraph. Experimental results show that our proposed method outperforms existing methods.

Keywords:
Hypergraph Subgraph isomorphism problem Isomorphism (crystallography) Induced subgraph isomorphism problem Computer science Graph isomorphism Theoretical computer science Graph Mathematics Database Combinatorics Line graph

Metrics

8
Cited By
0.43
FWCI (Field Weighted Citation Impact)
8
Refs
0.60
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Graph Theory and Algorithms
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Graph Neural Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Data Management and Algorithms
Physical Sciences →  Computer Science →  Signal Processing

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