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A unified framework for strengthening topological node features and its application to subgraph isomorphism detection

conference contribution
posted on 2013-01-01, 00:00 authored by N Dahm, H Bunke, Terry Caelli, Y Gao
This paper presents techniques to address the complexity problem of subgraph isomorphism detection on large graphs. To overcome the inherently high computational complexity, the problem is simplified through the calculation and strengthening of topological node features. These features can be utilised, in principle, by any subgraph isomorphism algorithm. The design and capabilities of the proposed unified strengthening framework are discussed in detail. Additionally, the concept of an n-neighbourhood is introduced, which facilitates the development of novel features and provides an additional platform for feature strengthening. Through experiments performed with state-of-the-art subgraph isomorphism algorithms, the theoretical and practical advantages of using these techniques become evident. © 2013 Springer-Verlag.

History

Pagination

11-20

Location

Vienna, Austria

Start date

2013-05-15

End date

2013-05-17

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783642382208

Language

eng

Publication classification

E1.1 Full written paper - refereed

Editor/Contributor(s)

Kropatsch WG, Artner NM, Haxhimusa Y, Jiang X

Title of proceedings

Graph-based representations in pattern recognition : 9th IAPR-TC-15 International Workshop, GbRPR 2013, Vienna, Austria, May 15-17, 2013. Proceedings

Event

Graph-based Representations in Pattern Recognition. Workshop (2013 : 9th : Vienna, Austria)

Publisher

Springer

Place of publication

Berlin, Germany

Series

Lecture Notes in Computer Science; 7877

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