Abstract
We investigate the characteristic of several intelligent algorithms for the program dialogue module of the support system of development personnel of high-tech service-oriented companies. Briefly describes the parametric model of workplace learning as base for personnel development and the most appropriate approaches to the formation of specific staff competencies. One of the elements of the proposed system is the means of answering personnel professional questions. In such applications, an important role is played by means of preliminary classification of queries that allow to narrow the search domain and increase the relevance. Three approaches to classifying of questions were compared: The Naive Bayes classifier, Random Forest Classifier and neural network. A comparative assessment of such approaches was carried out.
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2011 ITIL v3 (IT Infrastructure Library v3 2011 Edition).
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This work was supported by Russian Science Foundation, Grant #19-19-00696.
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Beresnev, A., Gusarova, N. (2020). Comparison of Intelligent Classification Algorithms for Workplace Learning System in High-Tech Service-Oriented Companies. In: Alexandrov, D.A., Boukhanovsky, A.V., Chugunov, A.V., Kabanov, Y., Koltsova, O., Musabirov, I. (eds) Digital Transformation and Global Society. DTGS 2020. Communications in Computer and Information Science, vol 1242. Springer, Cham. https://doi.org/10.1007/978-3-030-65218-0_27
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