Abstract
A system based on the adaptation of the search principle used in ant colony optimization (ACO) for multiobjective graph-based data mining (GBDM) is introduced in this paper. Our multiobjective ACO algorithm is designed to retrieve the best substructures in a graph database by jointly considering two criteria, support and complexity. The experimental comparison performed with a classical GBDM method shows the good performance of the new proposal on three datasets.
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Cordón, O., Quirin, A., Romero-Zaliz, R. (2010). Multiple Ant Colony System for Substructure Discovery. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2010. Lecture Notes in Computer Science, vol 6234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15461-4_46
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DOI: https://doi.org/10.1007/978-3-642-15461-4_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15460-7
Online ISBN: 978-3-642-15461-4
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