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In this paper AI agents for natural language interfaces in data exploration domain are presented. The experiment done with the IBM natural language toolbox has shown that the black box approach in this case leads to misclassification. Unsatisfactory results of the experiment triggered the present research aimed at improving the user interface with the natural language modality at architectural and algorithm levels. We extended traditional natural language interfaces in data exploration domain in the following direction: the use of feedforward neural network as concepts indexes in the users natural language interfaces are suggested. All presented concepts are realized as the open source project JMining Dialog.

THE USE OF THE NATURAL LANGUAGE UNDERSTANDING AGENTS WITH CONCEPTUAL MODELS