This study aims to segment the market based on demographical, psychological, and behavioral variables, and seeks to investigate their relationship with green consumer behavior. In this research, self-organizing maps are used to segment and to determine the features of green consumer behavior. This was a survey type of research study in which eight variables were selected from the demographical,...

An overview on the usage of emergent self organizing maps is given. U-Maps visualize the distance structures of high dimensional data sets. P-Maps show their density structures and U*-Maps combine the advantages of the mentioned maps to a visualization suitable to detect nontrivial cluster structures. A concise summary on the usage of Emergent Self-organizing Maps (ESOM) for data mining is give...

Semantic multimedia organization is an open challenge. In this chapter, we present an innovative way of automatically organizing multimedia information to facilitate content-based browsing. It is based on self-organizing maps. The visualization capabilities of the self-organizing map provide an intuitive way of representing the distribution of data as well as the object similarities. The main i...

The limitations of using self-organizing maps (SOM) for either clustering/vector quantization (VQ) or multidimensional scaling (MDS) are being discussed by reviewing recent empirical ndings and the relevant theory. SOM's remaining ability of doing both VQ and MDS at the same time is challenged by a new combined technique of online K-means clustering plus Sammon mapping of the cluster centroids....

In a number of real-life applications, the user is interested in analyzing several sources of information together: a graph combined with the additional information known on its nodes, numerical variables measured on individuals and factors describing these individuals... The combination of all sources of information can help him to understand the dataset in its whole better. The present articl...

We introduce a novel system of interconnected SelfOrganizing Maps that can be used to build feedforward and recurrent networks of maps. Prime application of interconnected maps is in modelling systems that operate with multimodal data as for example in visual and auditory cortices and multimodal association areas in cortex. A detailed example of animal categorization in which the feedworward ne...

Neural maps are a very popular class of unsupervised neural networks that project high-dimensional data of the input space onto a neuron position in a low-dimensional output space grid. It is desirable that the projection effectively preserves the structure of the data. In this paper we present a hybrid model called K-Dynamical Self Organizing Maps (KDSOM ) consisting of K Self Organizing Maps ...