Topographic maps are an appealing exploratory instrument for discovering new knowledge from databases. During the recent years, several variations on the Self Organizing Maps (SOM) were introduced in the literature. In this paper, the toroidal Emergent SOM tool and the spherical SOM are used to analyze a text corpus consisting of police reports of all violent incidents that occurred during the ...

In the paper, text mining and visualization by self-organizing map (SOM) are investigated. At first, textual information must be converted into numerical one. The results of text mining and visualization depend on the conversion. So, the influence of some control factors (the common word list and usage of the stemming algorithm) on text mining results, when a document dictionary is created, is ...

Recently, security of the computer systems becomes an important problem. Almost all computers use the password mechanism for the user authentication. But password mechanism has many issues. In this paper, we propose a kind of biometrics authentication method using the combinations of key stroke timings and pen calligraphy. For this method, selection of the phrase is important. We analyzed the k...

A slow oscillatory movement (SOM) has previously been discovered superimposed on the three well known components of fixational eye movements. The purpose of the present study was to explore the visual influence on the control mechanism of the SOM. Three tests with different fixation targets and backgrounds were prepared. The eye position during a fixation task on healthy test subjects has been ...

The Self-Organizing Map, SOM, is a widely used tool in exploratory data analysis. A major drawback of the SOM has been the lack of a theoretically justified criterion for model selection. Model complexity has a decisive effect on the reliability of visual data analysis, which is a main application of the SOM. In particular, independence of variables cannot be observed unless generalization of t...

In this paper the "Self-Organizing (Feature) Map" (SOM) methodology as originally proposed by Kohonen (1982) is employed in the context of Competitive Market Structure (CMS) and segmentation analysis using household-speci c brands preferences derived from diary panel data as input patterns for SOM training. The adaptive SOM algorithm results in a representation of competitive structures among r...

Several methods to visualize clusters in high-dimensional data sets using the Self-Organizing Map (SOM) have been proposed. However, most of these methods only focus on the information extracted from the model vectors of the SOM. This paper introduces a novel method to visualize the clusters of a SOM based on smoothed data histograms. The method is illustrated using a simple 2-dimensional data ...

The self organizing map SOM is a method that represents statistical data sets in an ordered fashion as a natural groundwork on which the distributions of the individual indicators in the set can be displayed and analyzed As a case study that instructs how to use the SOM to compare states of economic systems the standard of living of dif ferent countries is analyzed using the SOM Based on a grea...

Touch-free gesture technology opens new avenues for human-machine interaction. We show how self-organizing maps (SOM) can be used for hand and full body tracking. We use a range camera for data acquisition and apply a SOM-learning process for each frame in order to capture the pose. In a next step we introduce an extension of the SOM to 1D and 2D segments for an improved representation and skel...

PROPRE is a generic and semi-supervised neural learning paradigm that extracts meaningful concepts of multimodal data flows based on predictability across modalities. It consists on the combination of two computational paradigms. First, a topological projection of each data flow on a self-organizing map (SOM) to reduce input dimension. Second, each SOM activity is used to predict activities in ...