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Inexact graph matching using eigen-subspace projection clustering

journal contribution
posted on 2004-05-01, 00:00 authored by Terry Caelli, S Kosinov
Graph eigenspaces have been used to encode many different properties of graphs. In this paper we explore how such methods can be used for solving inexact graph matching (the matching of sets of vertices in one graph to those in another) having the same or different numbers of vertices. In this case we explore eigen-subspace projections and vertex clustering (EPS) methods. The correspondence algorithm enables the EPC method to discover a range of correspondence relationships from one-to-one vertex matching to that of inexact (many-to-many) matching of structurally similar subgraphs based on the similarities of their vertex connectivities defined by their positions in the common subspace. Examples in shape recognition and random graphs are used to illustrate this method.

History

Journal

International Journal of Pattern Recognition and Artificial Intelligence

Volume

18

Pagination

329-354

ISSN

0218-0014

eISSN

1793-6381

Language

English

Publication classification

C1 Refereed article in a scholarly journal

Issue

3

Publisher

WORLD SCIENTIFIC PUBL CO PTE LTD