This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
This paper extends a previous model where we examined the markets’ microstructure dynamics by using Genetic Programming as a trading rule inference engine, and Self Organizing Ma...
Michael Kampouridis, Shu-Heng Chen, Edward P. K. T...
Abstract. In this paper, we present an approach for musical artist recommendation based on Self-Organizing Maps (SOMs) of artist reviews from Amazon web site. The Amazon reviews fo...
Abstract. Self-Organizing Maps (SOM) is a powerful tool for clustering and discovering patterns in data. Competitive learning in the SOM training process focusses on finding a neu...
Self-Organizing Maps (SOMs) have been used to visualize tradeoffs of Pareto solutions in the objective function space for engineering design obtained by Evolutionary Computation. F...