Es besteht ein hohes Interesse an Techniken zur Analyse von Anwendungslandschaften. Im Sinne eines Portfoliomanagements sind für diese Aufgabe häufig mehrere Dimensionen relevant. Werden Kennzahlen verwendet, entstehen multidimensionale Datensätze, die sich bei einer sehr großen Anzahl an Elementen mittels konventioneller Techniken nur noch schwer erschließen lassen. Die SelfOrganizing Map (SOM...

The Self-Organizing Map (SOM) enjoys significant popularity in the field of data mining and visualization. While its topology-preserving mapping allows easier interpretation of complex data, communicating the location of clusters and individual data items as well as memorizing locations are not solved satisfactorily in conventional rectangular maps. In this paper, a variant of self-organizing m...

This paper presents an innovative, adaptive variant of Kohonen’s selforganizing maps called ASOM, which is an unsupervised clustering method that adaptively decides on the best architecture for the self-organizing map. Like the traditional SOMs, this clustering technique also provides useful information about the relationship between the resulting clusters. Applications of the resulting softwar...

In this paper, we present Kohonen Self-Organizing Feature Maps (SOMs) as a method for automatically nding classes of dialogue utterances on the basis of superrcial utterance features, in particular for dialogues found in the Schisma corpus. Furthermore, we discuss some ways for determining the quality of a certain utterance classiication. We propose to use supervised classiication to gain more ...

This paper is about different techniques for intelligent processing of data obtained with water quality monitoring distributed systems. The techniques include a set of fuzzy neural networks (FuNNs) for modelling measuring channels and Kohonen Self Organizing Maps (K-SOMs) for information classification. Elements of FuNN and K-SOM optimization in terms of architecture and training are presented ...

Low-frequency oscillations (<0.08 Hz) have been detected in functional MRI studies, and appear to be synchronized between functionally related areas. A current challenge is to detect these patterns without using an external reference. Self-organizing maps (SOMs) offer a way to automatically group data without requiring a user-biased reference function or region of interest. Resting state functi...

Resistance spot welding is used to join two or more metal objects together, and the technique is in widespread use in, for example, the automotive and electrical industries. This paper discusses both the identification of different spot welding processes and the process initialization parameters leading to highquality welding joints. In this research, self-organizing maps (SOMs) were used, and ...

In this work, we applied a stochastic simulation methodology to quantify the power of detection outlying mixture components model, when applying reduced-dimension clustering technique such as Self-Organizing Maps (SOMs). The essential feature SOMs, besides dimensional reduction into discrete map, is conservation topology. two forms learning are applied: competitive, by sequential allocation sam...

In this work, we will report on the use of selforganizing maps (SOMs) in a clustering and relation extraction task. Specifically, we use the approach of self-organizing maps for structured data (SOMSDs) (i) for clustering music related articles from the free online encyclopedia Wikipedia and (ii) for extracting relations between the created clusters. We hereby rely on the bag-of-words similarit...