Subgraph Isomorphism Search in Massive Graph Databases
Résumé
Subgraph isomorphism search is a basic task in querying graph data. It consists to find all embeddings of a
query graph in a data graph. It is encountered in many real world applications that require the management
of structural data such as bioinformatics and chemistry. However, Subgraph isomorphism search is an NPcomplete
problem which is prohibitively expensive in both memory and time in massive graph databases. To
tackle this problem, we propose a new approach based on concepts widely different from existing works. Our
approach relies on a summarized representation of the graph database that minimizes both the amount space
required to store data graphs and the processing time of querying them. Experimental results show that our
approach performs well compared to the most efficient approach of the literature.
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