On efficient graph substructure selection

Abstract

Graphs have a wide range of applications in many domains. The graph substructure selection problem is to find all subgraph isomorphic mappings of a query from multi-attributed graphs, such that each pair of matching vertices satisfy a set of selection conditions, each against an equality, range, or set containment operator on a vertex attribute. Existing techniques for single-labeled graphs are developed under the assumption of identical label matching, and thus, cannot handle the general case in substructure selections. To this end, this paper proposes a two-tier index to support general selections via judiciously materializing certain mappings. Moreover, we propose efficient dynamic query processing and index construction algorithms. Comprehensive experiments demonstrate the effectiveness and efficiency of our approach. © Springer-Verlag 2013.