Efficient Searching of Subhypergraph Isomorphism in Hypergraph Databases

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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.
Publisher
IEEE
Issue Date
2018-01-17
Language
English
Citation

2018 IEEE International Conference on Big Data and Smart Computing (BigComp), pp.739 - 742

DOI
10.1109/BigComp.2018.00140
URI
http://hdl.handle.net/10203/240127
Appears in Collection
CS-Conference Papers(학술회의논문)
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