A Survey on Recent Advances in Self-Organizing Maps
Neural and Evolutionary Computing
2025-01-16 v1 Artificial Intelligence
Abstract
Self-organising maps are a powerful tool for cluster analysis in a wide range of data contexts. From the pioneer work of Kohonen, many variants and improvements have been proposed. This review focuses on the last decade, in order to provide an overview of the main evolution of the seminal SOM algorithm as well as of the methodological developments that have been achieved in order to better fit to various application contexts and users' requirements. We also highlight a specific and important application field that is related to commercial use of SOM, which involves specific data management.
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Cite
@article{arxiv.2501.08416,
title = {A Survey on Recent Advances in Self-Organizing Maps},
author = {Axel Guérin and Pierre Chauvet and Frédéric Saubion},
journal= {arXiv preprint arXiv:2501.08416},
year = {2025}
}
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36 pages