WSOM: Building Adaptive Wavelets with Self-organizing Maps

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

Concept Mining with Self-Organizing Maps for the Semantic Web

In this paper, we discuss problems related to the basic Semantic Web methodologies that are based on predicate logic and related formalisms. We discuss complementary and alternative approaches. In particular, we suggest how the Self-Organizing Map can be a basis for making the Semantic Web more semantic.

Top-Down Control of Learning in Biological Self-Organizing Maps

This paper discusses biological aspects of self-organising maps (SOMs) which includes a brief review of neurophysiological findings and classical models of neurophysiological SOMs. We then discuss some simulation studies on the role of topographic map representation for training mapping networks and on top-down control of map plasticity.

SOMbrero: An R Package for Numeric and Non-numeric Self-Organizing Maps

This paper presents SOMbrero, a new R package for selforganizing maps. Along with the standard SOM algorithm for numeric data, it implements self-organizing maps for contingency tables (“Korresp”) and for dissimilarity data (“relational SOM”), all relying on stochastic (i.e., on-line) training. It offers many graphical outputs and diagnostic tools, and comes with a user-friendly web graphical i...