A Survey on Recent Advances in Self-Organizing Maps
It provides an overview for researchers and practitioners interested in SOM improvements, but it is incremental as it synthesizes existing work.
This survey reviews recent advances in Self-Organizing Maps (SOMs) over the last decade, covering algorithmic evolutions and methodological developments to adapt to various applications, including commercial uses with specific data management.
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.