A hierarchically growing hyperbolic self-organizing map for rapid structuring of large data sets

Large-scale data exploration with the hierarchically growing hyperbolic SOM

We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that allows for incremental training with an automated adaptation of lattice size to achieve a prescribed quantization error and (ii) an approximate best match search that utilizes the special structure of the hyperbolic latti...

Semantic visualization with hyperbolic self-organizing maps: a novel approach for exploring structure in large data sets

A Modfied Self-organizing Map Neural Network to Recognize Multi-font Printed Persian Numerals (RESEARCH NOTE)

This paper proposes a new method to distinguish the printed digits, regardless of font and size, using neural networks.Unlike our proposed method, existing neural network based techniques are only able to recognize the trained fonts. These methods need a large database containing digits in various fonts. New fonts are often introduced to the public, which may not be truly recognized by the Opti...

Applications of the Growing Self Organizing Map on High Dimensional Data

The Growing Self Organizing Map (GSOM) is a dynamic variant of the Self Organizing Map (SOM). It has been mainly used on low dimensional data sets. In this paper the GSOM is applied on high dimensional data sets and its performance is evaluated. Several modifications to the original GSOM algorithm are presented that enable the GSOM to be applied on high dimensional data .The modified version of...

User Modelling for Interactive User-Adaptive Collection Structuring

Automatic structuring is one means to ease access to document collections, be it for organization or for exploration. Of even greater help would be a presentation that adapts to the user’s way of structuring and thus is intuitively understandable. We extend an existing useradaptive prototype system that is based on a growing self-organizing map and that learns a feature weighting scheme from a ...