Michael Dittenbach

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The self-organizing map (SOM) is a very popular unsupervised neural-network model for the analysis of high-dimensional input data as in data mining applications. However, at least two limitations have to be noted, which are related to the static architecture of this model as well as to the limited capabilities for the representation of hierarchical(More)
With the rising popularity of digital music archives the need for new access methods such as interactive exploration or similarity-based search become significant. In this paper we present the PlaySOM, as well as the PocketSOMPlayer, two novel interfaces allowing to browse a music collection by navigating a map of clustered music tracks and to select(More)
The Self-Organizing Map is a very popular unsupervised neural network model for the analysis of high-dimensional input data as in data mining applications. However, at least two limitations have to be noted, which are caused, on the one hand, by the static architecture of this model, as well as, on the other hand, by the limited capabilities for the(More)
The self-organizing map has shown to be a stable neural network model for high-dimensional data analysis. However, its applicability is limited by the fact that some knowledge about the data is required to de ne the size of the network. In this paper we present the Growing Hierarchical SOM. This dynamically growing architecture evolves into a hierarchical(More)
In recent years a technological and sociological paradigm shift has taken place in the Internet that is often referred to as Web 2.0. Companies and individuals have started to adapt existing Web sites to the new standards and principles and created new types of Web services and communities. The tourism domain is no exception to this trend new tourism(More)
In this paper we present the application of the SOMLib digital library system to a multilingual document corpus from the Russian Information Agency Novosti. News articles in Russian, English, and German are automatically organized into separate topic hierarchies using a novel unsupervised neural network, namely the Growing Hierarchical Self-Organizing Map.(More)
In several application domains research in natural language processing and information extraction has spawned valuable tools that support humans in structuring, aggregating and managing large amounts of information available as text. Patent claims, although subject to a number of rigid constraints and therefore forced into foreseeable structures, are(More)