Decision Support via Big Multidimensional Data Visualization.
Audronė Lupeikienė, Viktor Medvedev, Olga Kurasova, Albertas Čaplinskas, Gintautas Dzemyda · 2015
Business information systems nowadays should be thought of first of all as the decision-oriented systems supported by different types of subsystems. Multidimensional data visualization is an essential constituent of such systems, especially in the age of growing amounts of data to be interpreted and analyzed. As managers are faced with a federated environment and need to make timecritical decisions, data should be presented in a meaningful manner and easily understandable form. It is required more effective ways to cope with this situation. One of them is the visual presentation of complex data for human decisions. The paper focuses on the neural networks-based methods for visualization of big multidimensional datasets. The new strategy – to decrease the number of cycles of data reviews (passes of training data) up to the only one when training neural networks is proposed. The results of experiment on benchmark data to test this strategy are presented.