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Graphs are widely used to model complex data in many applications, such as bioinformatics, chemistry, social networks, pattern recognition, etc. A fundamental and critical query primitive is to efficiently search similar structures in a large collection of graphs. This paper studies the graph similarity queries with edit distance constraints. Existing solutions to the problem utilize fixed-size overlapping substructures to generate candidates, and thus become susceptible to large vertex degreesdoi:10.14778/2732232.2732236 fatcat:yu4do4by7rgfhemjgm7edusf4u