SING: subgraph search in non-homogeneous graphs.
BACKGROUND
Finding the subgraphs of a graph database that are isomorphic to a given query graph has practical applications in several fields, from cheminformatics to image understanding. Since subgraph isomorphism is a computationally hard problem, indexing techniques have been intensively exploited to speed up the process. Such systems filter out those graphs which cannot contain the query, and apply a subgraph isomorphism algorithm to each residual candidate graph. The applicability of such systems is limited to databases of small graphs, because their filtering power degrades on large graphs.


RESULTS
In this paper, SING (Subgraph search In Non-homogeneous Graphs), a novel indexing system able to cope with large graphs, is presented. The method uses the notion of feature, which can be a small subgraph, subtree or path. Each graph in the database is annotated with the set of all its features. The key point is to make use of feature locality information. This idea is used to both improve the filtering performance and speed up the subgraph isomorphism task.


CONCLUSIONS
Extensive tests on chemical compounds, biological networks and synthetic graphs show that the proposed system outperforms the most popular systems in query time over databases of medium and large graphs. Other specific tests show that the proposed system is effective for single large graphs.
Di Natale
Raffaele
R
Dipartimento di Matematica ed Informatica, Università di Catania, Catania, Italy.
Ferro
Alfredo
A
Giugno
Rosalba
R
Mongiovì
Misael
M
Pulvirenti
Alfredo
A
Shasha
Dennis
D
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D016208:Databases, Factual; D030562:Databases, Protein; D016247:Information Storage and Retrieval / Q000379:methods; D012984:Software; D014584:User-Computer Interface