Efficient searching of subhypergraph isomorphism in hypergraph databases

Abstract

A hypergraph consisting of vertices and hyperedges that connect multiple vertices can model complex relationships among entities effectively. In this work, we study a searching of subhypergraph isomorphism 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 thesis, we propose a method that finds subhypergraph isomorphism efficiently. We first select vertices and hyperedges 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.