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Authors: Anthony Gillioz 1 and Kaspar Riesen 2 ; 1

Affiliations: 1 Institute of Computer Science, University of Bern, Bern, Switzerland ; 2 Institute for Informations Systems, University of Appl. Sci. Northwestern Switzerland, Olten, Switzerland

Keyword(s): Structural Pattern Recognition, Graph Matching, Genetic Algorithm, Multiple Classifier Systems.

Abstract: The development and research of graph-based matching techniques that are both computationally efficient and accurate is a pivotal task due to the rapid growth of data acquisition and the omnipresence of structural data. In the present paper, we propose a novel framework using information gained from diversely reduced graph spaces to improve the classification accuracy of a structural classifier. The basic idea consists of three subsequent steps. First, the original graphs are reduced to different size levels with the aid of node centrality measures. Second, we compute the distances between the reduced graphs in the corresponding graph subspaces. Finally, the distances are linearly combined and fed into a distance-based classifier to produce the final classification. On six graph datasets we empirically demonstrate that classifiers clearly benefit from the combined distances obtained in the graph subspaces.

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Paper citation in several formats:
Gillioz, A. and Riesen, K. (2022). Improving Graph Classification by Means of Linear Combinations of Reduced Graphs. In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-549-4; ISSN 2184-4313, SciTePress, pages 17-23. DOI: 10.5220/0010776900003122

@conference{icpram22,
author={Anthony Gillioz. and Kaspar Riesen.},
title={Improving Graph Classification by Means of Linear Combinations of Reduced Graphs},
booktitle={Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2022},
pages={17-23},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010776900003122},
isbn={978-989-758-549-4},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Improving Graph Classification by Means of Linear Combinations of Reduced Graphs
SN - 978-989-758-549-4
IS - 2184-4313
AU - Gillioz, A.
AU - Riesen, K.
PY - 2022
SP - 17
EP - 23
DO - 10.5220/0010776900003122
PB - SciTePress

- Science and Technology Publications, Lda.
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