Self-organizing maps (SOM) have been recognized as a powerful tool in data exploratoration, especially for the tasks of clustering on high dimensional data. However, clustering on categorical data is still a challenge for SOM. This paper aims to extend standard SOM to handle feature values of categorical type. A batch SOM algorithm (NCSOM) is presented concerning the dissimilarity measure and update method of map evolution for both numeric and categorical features simultaneously
Kohonen Self Organizing Maps (SOM) has found application in practical all fields, especially those w...
Abstract—The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It ...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. It is capa...
International audienceThe self-organizing map is a kind of artificial neural network used to map hig...
The Self-Organizing Maps (SOM) is a very popular algorithm, introduced by Teuvo Kohonen in the early...
International audienceThe self-organizing map is a kind of artificial neural network used to map hig...
ISBN : 978-1-59904-849-9 ; 11 pagesAdaptation of the Self-Organizing Map to dissimilarity data is of...
Nowadays, lots of data is being collected for different industrial and commercial purposes, where th...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. However, d...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. It is capa...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. It is capa...
International audienceIn this paper, we present a new heuristic measure for optimizing database used...
Clustering is to group similar objects into clusters. Until now there are a lot of approaches using ...
Abstract. In some applications and in order to address real world sit-uations better, data may be mo...
Kohonen Self Organizing Maps (SOM) has found application in practical all fields, especially those w...
Abstract—The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It ...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. It is capa...
International audienceThe self-organizing map is a kind of artificial neural network used to map hig...
The Self-Organizing Maps (SOM) is a very popular algorithm, introduced by Teuvo Kohonen in the early...
International audienceThe self-organizing map is a kind of artificial neural network used to map hig...
ISBN : 978-1-59904-849-9 ; 11 pagesAdaptation of the Self-Organizing Map to dissimilarity data is of...
Nowadays, lots of data is being collected for different industrial and commercial purposes, where th...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. However, d...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. It is capa...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. It is capa...
International audienceIn this paper, we present a new heuristic measure for optimizing database used...
Clustering is to group similar objects into clusters. Until now there are a lot of approaches using ...
Abstract. In some applications and in order to address real world sit-uations better, data may be mo...
Kohonen Self Organizing Maps (SOM) has found application in practical all fields, especially those w...
Abstract—The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It ...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. It is capa...
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