Gillioz, Anthony; Riesen, Kaspar (2023). Building Multiple Classifier Systems Using Linear Combinations of Reduced Graphs. SN computer science, 4(6), p. 743. Springer 10.1007/s42979-023-02194-1
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Despite great efforts done in research in the last decades, the classification of general graphs, i.e., graphs with unconstrained labeling and structure, remains a challenging task. Due to the inherent relational structure of graphs it is difficult, or even impossible, to apply standard pattern recognition methods to graphs to achieve high recognition accuracies. Common methods to solve the non-trivial problem of graph classification employ graph matching in conjunction with a distance-based classifier or a kernel machine. In the present paper, we address the specific task of graph classification by means of a novel framework that uses information acquired from a broad range of reduced graph subspaces. Our novel approach can be roughly divided into three successive steps. In the first step, differently reduced graphs are created out of the original graphs relying on node centrality measures. In the second step, we compute the graph edit distance between each reduced graph and all the other graphs of the corresponding graph subspace. Finally, we linearly combine the distances in the third step and feed them into a distance-based classifier to obtain the final classification result. On six graph data sets, we empirically confirm that the proposed multiple classifier system directly benefits from the combined distances computed in the various graph subspaces.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
08 Faculty of Science > Institute of Computer Science (INF) |
UniBE Contributor: |
Gillioz, Anthony Daniel Francis, Riesen, Kaspar |
Subjects: |
000 Computer science, knowledge & systems 500 Science > 510 Mathematics |
ISSN: |
2661-8907 |
Publisher: |
Springer |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
03 Oct 2023 13:42 |
Last Modified: |
29 Oct 2023 02:25 |
Publisher DOI: |
10.1007/s42979-023-02194-1 |
PubMed ID: |
37781341 |
Uncontrolled Keywords: |
Genetic algorithm Graph matching Multiple classifier systems Structural pattern recognition |
BORIS DOI: |
10.48350/186854 |
URI: |
https://boris.unibe.ch/id/eprint/186854 |
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