Inexact graph matching using eigen-subspace projection clustering

Caelli, Terry and Kosinov, Serhiy 2004, Inexact graph matching using eigen-subspace projection clustering, International Journal of Pattern Recognition and Artificial Intelligence, vol. 18, no. 3, pp. 329-354, doi: 10.1142/S0218001404003186.


Title Inexact graph matching using eigen-subspace projection clustering
Author(s) Caelli, TerryORCID iD for Caelli, Terry orcid.org/0000-0001-9281-2556
Kosinov, Serhiy
Journal name International Journal of Pattern Recognition and Artificial Intelligence
Volume number 18
Issue number 3
Start page 329
End page 354
Total pages 26
Publisher WORLD SCIENTIFIC PUBL CO PTE LTD
Publication date 2004-05-01
ISSN 0218-0014
1793-6381
Keyword(s) Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science
inexact graph matching
eigendecomposition
eigen-subspace projections
correspondence clustering
shape matching
relational information retrieval
ALGORITHM
ISOMORPHISM
Summary 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.
Language eng
DOI 10.1142/S0218001404003186
Indigenous content off
Field of Research 0801 Artificial Intelligence and Image Processing
1702 Cognitive Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30138431

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