Matching shape graphs

Abstract

Graphs are important structures to model complex relationships such as chemical compounds, proteins, geometric or hierarchical parts, and XML documents. Given a query graph, indexing has become a necessity to retrieve similar graphs quickly from large databases. We propose a novel technique for indexing databases, whose entries can be represented as graph structures. Our method starts by representing the topological structure of a graph as well as that of its subgraphs as vectors in which the components correspond to the sorted laplacian eigenvalues of the graph or subgraphs. By doing a nearest neighbor search around the query spectra, similar but not necessarily isomorphic graphs are retrieved.