Manuel Rubio, Vı́ctor Giménez, Francisco Dı́az and Pedro Gómez 1 Departamento de Arquitectura y Tecnologı́a de Sistemas Informáticos 2 Departamento de Matemática Aplicada Facultad de Informática, Universidad Politécnica de Madrid Campus de Montegancedo, 28660 Boadilla del Monte, Madrid, Spain [email protected], [email protected] [email protected], [email protected]...

Current research on machine learning and related algorithms is focused mainly on numeric paradigms. It is, however, widely supposed that intelligent behavior strongly relies on ability to manipulate symbols. In this paper we present on-line versions of self-organizing maps for symbol strings. The underlying key concepts are average and similarity, applied on strings. These concepts are easily d...

Searching for relevant text documents has traditionally been based on keywords and Boolean expressions of them. Often the search results show high recall and low precision, or vice versa. Considerable eeorts have been made to develop alternative methods, but their practical applicability has been low. Powerful methods are needed for the exploration of miscellaneous document collections. The WEB...

Self-organizing maps (SOM) are a powerful tool for detecting patterns in large, multi-dimensional data sets. Additional visualization techniques have been developed to support the user to gain insight into its structure. For complex data sets, even these techniques are not easily interpretable. Most of them consist of a grid where each cell contains a single value. Such a structure can be seen ...

We present a new neural classification model called Concurrent Self-Organizing Maps (CSOM), representing a winner-takes-all collection of small SOM networks. Each SOM of the system is trained individually to provide best results for one class only. We have considered two significant applications: face recognition and multispectral satellite image classification. For first application, we have u...

An interactive face retrieval system that uses selforganizing maps and user feedback is described. The system solves some problems of related content-based image retrieval systems: non-existence of trivial high-level human descriptions of the images and the gap between the high-level descriptions and the low-level features used to index the images.

We have developed a method that utilizes hypertext link information in image retrieval from the World Wide Web. The basis of the method consists of a set of basic relations that can take place between two images in the Web. Our method uses the SHA-1 message digest algorithm for dimension reduction by random mapping. The Web link features have then been used in creating a SelfOrganizing Map of i...

Unsupervised neural networks such as the Kohonen Self-Organizing Maps (SOM) have been widely used for searching natural clusters in multidimensional and massive data. One example where the data available for analysis can be extremely large is seismic interpretation for hydrocarbon exploration. In order to assist the interpreter in identifying characteristics of interest confined in the seismic ...