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Decision Trees for Error-Tolerant Graph Database Filtering

  • Conference paper
Graph-Based Representations in Pattern Recognition (GbRPR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3434))

Abstract

An important topic in pattern recognition is retrieval of candidate patterns from a database according to a given sample input pattern. Using graphs, the database retrieval problem is turned into a graph matching problem. In this paper we propose a method based on decision trees to filter a database of graphs according to a given input graph. The present paper extends previous work concerned with graph and subgraph isomorphism to the case of error-tolerant graph matching.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Bern, Neubrückstrasse 10, CH-3012, Bern, Switzerland

    Christophe Irniger & Horst Bunke

Authors
  1. Christophe Irniger
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  2. Horst Bunke
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Editor information

Editors and Affiliations

  1. GREYC CNRS UMR 6072, Image Team, Université de Caen Basse-Normandie, 6, Boulevard Maréchal Juin, 14050, Caen Cedex, France

    Luc Brun

  2. Dipartimento di Ingegneria dell’Informazione ed Ingegneria Elettrica, Università di Salerno, via P.te Don Melillo, I-84084, Fisciano, SA), Italy

    Mario Vento

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© 2005 Springer-Verlag Berlin Heidelberg

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Irniger, C., Bunke, H. (2005). Decision Trees for Error-Tolerant Graph Database Filtering. In: Brun, L., Vento, M. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2005. Lecture Notes in Computer Science, vol 3434. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31988-7_29

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  • DOI: https://doi.org/10.1007/978-3-540-31988-7_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25270-2

  • Online ISBN: 978-3-540-31988-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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