FEATURES OF CONSTRUCTION AND BASIC DIRECTIONS OF DEVELOPMENT OF VIRTUAL DIGITAL ASSISTANTS

Authors

DOI:

https://doi.org/10.28925/2663-4023.2020.9.140148

Keywords:

virtual assistant machine learning; conceptual model; essence; attribute; software

Abstract

The article analyzes the main aspects of creating virtual assistants that are part of intelligent computer programs – artificial intelligence systems (AI). The main task of “artificial intelligence” is to ensure effective communication of intelligent robotic systems (including unmanned vehicles) with humans. The basis of the above is in-depth training (systematic machine translation, speech recognition, processing of complex texts in natural languages, computer vision, automation of driving, etc.). This machine learning subsystem can be characterized using neural network models that mimic the brain. Any neural network model learns from large data sets, so it acquires some “skills”, but how it uses them remains for engineers, which ultimately becomes one of the most important problems for many deep learning applications. The reason is that such a model is formal and without an understanding of the logic of its actions. This raises the question: is it possible to increase the level of trust in such systems based on machine learning? Machine learning algorithms are complex mathematical descriptions and procedures and have a growing impact on people's lives. As the decision is increasingly determined by the algorithms, they become less transparent and understandable. Based on the foregoing, the paper considers the issues of the technological component and the algorithms of virtual digital assistants, conducts information modeling based on the conceptual model of the interaction of the virtual assistant with the database, and analyzes the scope and further development of the IT-sphere.

Downloads

Download data is not yet available.

References

Vorobienko P.P., Punchenko О.P. (2010). The theoretical foundations of the formation of modern information civilization. Philosophy and Social Sciences: Scientific Journal, (1), p. 65-71. https://elib.bsu.by/handle/123456789/7965.

Vorobienko P.P., Nikityuk L.A., Reznіchenko P.І. (2010). Telecommunication and information networks. SAMMIT-BOOK.

Sutton R. and Barto A. (2012). Reinforcement Learning an Introduction. The MIT Press Cambridge, Massachusetts London, England.

Spasiteleva S., Buriachok V. (2018). Perspectives for development of blockchain applications in Ukraine. Cybersecurity: education, science, technique, 1(1), p. 35-48. https://doi.org/10.28925/2663-4023.2018.1

Heineman D., Pollis G., Selkov S. (2017). Algorithms. Reference with examples on С, С++, Java and Python. (Selkov S., Eds.). Williams Publishing House. (The original has been published at 2017).

Poibeau Th., Saggion H., Piskorski J. (2013). Multi-source, multilingual information extraction and summarization, Theory and Applications of Natural Language Processing, Springer-Verlag (Yangarber R., Eds.). Berlin–Heidelberg.

Fowler M. (2007). Architecture of corporate software applications. Williams Publishing House.

Jing H., Haihong E., Guan L., Jian D. (2011). Survey on NoSQL database. Pervasive Computing and Applications (ICPCA), 6th International Conference, p. 363–366. https://doi.org/10.1109/ICPCA.2011.6106531

Chan W. (2017). Python: application creation. Professional Library. Williams Publishing House.

Deep Learning Market by Application (Image Recognition, Signal Recognition, Data Mining), Offering (Hardware (Von Neumann and Neuromorphic Chip), and Software), End-User Industry, and Geography – Global Forecasts to 2022 / Markets and Markets. https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=107369271

Downloads


Abstract views: 415

Published

2020-09-24

How to Cite

Tsyra, O. ., Punchenko, N. ., & Fraze-Frazenko , O. . (2020). FEATURES OF CONSTRUCTION AND BASIC DIRECTIONS OF DEVELOPMENT OF VIRTUAL DIGITAL ASSISTANTS. Electronic Professional Scientific Journal «Cybersecurity: Education, Science, Technique», 1(9), 140–148. https://doi.org/10.28925/2663-4023.2020.9.140148