RWTH Aachen University
In this paper, the authors proposed about the problem of clustering for large datasets with high-dimensions. The authors propose a two-phase combined method with regard to high dimensions and exploiting the standard clustering algorithm. The first step of the method is based on the learning phase using artificial neural network, especially self organizing map, which they find as a suitable method for the reduction of the problem complexity. Due to the fact, that the learning phase of artificial neural networks can be time-consuming operation (especially for large high-dimensional datasets), they decided to accelerate this phase using parallelization to improve the computational efficiency.