Experience of use of neural networks in the analysis and the structural reconstruction of subject knowledge of the specialist

The paper reviews in a specific context of subjective field of knowledge the construction of graphic semantic model of that field. With the use of this model the task of automated analysis of current state of graph of knowledge of examinee (trainee) is considered. The result of analysis is the indication of gaps of knowledge - fell out elements and links of the graphic semantic model, which allows to recover it with additional target-method training. As an instrument of the automatization authors propose to use neural networks of the perceptron type. Monitoring, diagnostics, knowledge recovery and individual learning material studying paths ensuring reliability of error detection, objective knowledge evaluation and adaptivity by means of knowledge recovery procedure are performed based on the results of neural-network testing.