Advances in Self Organising Maps

TL;DR

This paper reviews recent advances in Self-Organizing Maps (SOM), highlighting their widespread use in unsupervised learning, clustering, and visualization, and discusses developments presented at the WSOM 2005 conference.

Contribution

It provides a comprehensive overview of recent developments and applications of SOM, emphasizing the ongoing research and community efforts through the WSOM conferences.

Findings

SOM remains a popular tool for unsupervised learning and data visualization.

Over 5,000 publications have contributed to SOM research.

The WSOM conferences foster ongoing advancements in the field.

Abstract

The Self-Organizing Map (SOM) with its related extensions is the most popular artificial neural algorithm for use in unsupervised learning, clustering, classification and data visualization. Over 5,000 publications have been reported in the open literature, and many commercial projects employ the SOM as a tool for solving hard real-world problems. Each two years, the "Workshop on Self-Organizing Maps" (WSOM) covers the new developments in the field. The WSOM series of conferences was initiated in 1997 by Prof. Teuvo Kohonen, and has been successfully organized in 1997 and 1999 by the Helsinki University of Technology, in 2001 by the University of Lincolnshire and Humberside, and in 2003 by the Kyushu Institute of Technology. The Universit\'{e} Paris I Panth\'{e}on Sorbonne (SAMOS-MATISSE research centre) organized WSOM 2005 in Paris on September 5-8, 2005.