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Approaches to creating intelligent chatbots

I. Ushakova
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Description: The analysis of the approaches to creating chatbots has been completed; the current state and the preconditions for their demand in networks are considered. The relevance of the use of chatbots for human interaction and the virtual environment was justified. Classification of chatbots according to user types, types of interfaces, methods of access to the bot, purpose and principles of operation has been done. The advantages of learning chatbots are justified. Learning bots are developed on the basis of artificial intelligence solutions and use natural language processing and machine learning when building a dialogue. The principle of their work is based on an analysis of the dialogue to further improve their communication skills. Such bots are able to process natural language and correctly answer the questions posed. The possibilities of using neural networks and natural language processing technologies for learning chatbots are considered .The chatbot interaction model with the messenger platform, which includes: the program itself, the client platform to the bot and the linking part, was built. The analysis of tools for creation of chatbots (frameworks, platforms, and analytics) has been raised; special attention is paid to the analysis of free tools. It was proposed to use the Long Short Term Memory neural network with short and long memory to take into account the context of the dialogue depending on the keywords. The basic steps in creating chatbots (definition of requirements, chatbot development, connection, analysis of work and refinement) and their content were defined. The results can be used by developers to create chatboots with artificial intelligence in various business and learning areas.

Keywords: chatbot, artificial intelligence, neural network, natural language processing, dialogue, tools


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 Ushakova, I.O. (2019), “Pidkhody do stvorennia intelektualnykh chat-botiv” [Approaches to creating intelligent chatbots], Information Processing Systems, Vol. 2(157), pp. 76-83. https://doi.org/10.30748/soi.2019.157.10.