WSOM 2005, Paris Self-Organizing Maps for Time Series

Editorial: Advances in Self-Organizing Maps

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 Universi...

Advances in Self-Organizing Maps

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 5000 publications have been reported in the open literature, and many commercial projects employ the SOM as a tool for solving hard real-world problems. Every two years, the “Workshop on Self-Organizin...

Theoretical and Applied Aspects of the Self-Organizing Maps

The Self-Organizing Map (SOM) is widely used, easy to implement, has nice properties for data mining by providing both clustering and visual representation. It acts as an extension of the k-means algorithm that preserves as much as possible the topological structure of the data. However, since its conception, the mathematical study of the SOM remains di cult and has be done only in very special...

Advances in Self-Organizing Maps

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-Organizi...

Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6-8, 2016