This paper deals with automatically learning the spatial distribution of a set of measurements: images, in the examples presented here. The solution to this problem can be viewed as an instance of robot mapping although it can also be used in other contexts. We examine the problem of organizing an ensemble of images of an environment in terms of the positions from which the images were obtained...

A topographic map is a two-dimensional, nonlinear approximation of a potentially high-dimensional data manifold, which makes it an appealing instrument for visualizing and exploring high-dimensional data. The Self-Organizing Map (SOM) is the most widely used algorithm, and it has led to thousands of applications in very diverse areas. In this chapter, we will introduce the SOM algorithm, discus...

− The concept of similarity is important for many data mining related applications such as content-based music retrieval. Defining similarity can be very difficult if several aspects are involved. For example, music similarity depends on the melody, rhythm, or instruments. The Self-Organizing Map is a powerful tool to visualize how the data looks like from a certain perspective of similarity. I...