A tutorial on neurocomputing of structures
Knowledge-based neurocomputing
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Networks for Adaptive Processing of Structured Data
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
The graph neural network model
IEEE Transactions on Neural Networks
A general framework for adaptive processing of data structures
IEEE Transactions on Neural Networks
A self-organizing map for adaptive processing of structured data
IEEE Transactions on Neural Networks
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The paper deals with Acyclic Graph Data Structures (AGDS) and with model of a self-organizing map (SOM) that has been modified for processing of AGDS. The motivation was found in the real world of the Academic Information System (AIS) at P. J. Šafárik University in Košice. To the modified SOM Neural Network (SOM NN), there are added contexts and counters which are built in a training phase of the neural network. The trained SOM NN in active phase can compute more information which is used to built an answer to some questions. The working application was tested on the study programs in informatics, the test results are very closed to the real values.