Чат-бот с использованием технологий нейронных сетей и методов обработки текста для повышения лояльности клиентов
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Chatbot based on neural networks and word embedding to increase customer loyalty

Kovalenko A.V.   Syusyura D.A.   Sharpan M.V.  

UDC 004.89
DOI: 10.26102/2310-6018/2022.37.2.014

  • Abstract
  • List of references
  • About authors

In the digital era mobile devices are becoming the main instrument of human social interaction. With the growing popularity of instant messengers, the role of chatbots in the mobile environment appears to be more and more significant. Intelligent interactive chatbots are often used in mobile applications and help improve the interaction between companies and their customers, which ultimately increases customer loyalty to that organization. Chatbots allow companies to communicate with customers on an individual basis, without involving employees and thereby saving time, money, and human resources. The majority of chatbots works with scripted algorithms and they are not universal. This is due to the simplicity and speed of development. However, in this case, there is a risk of missing many choices in the decision tree. Chatbots based on neural networks can solve this problem, but it should be taken into consideration that both of them have a drawback – long processing of messages and feedback. In the context of the scenario approach, this is caused by long branch transitions. For neural networks, complexity arises because of the feedback processing algorithm. In that instance, the application of the service will not be justified, customer loyalty to the organization will deteriorate. In this connection, the article discusses an alternative approach to creating chatbots with the aid of neural network technologies and text representation methods, which avoids the problems described above. As a means of chatbot design, the following technologies were utilized: Python 3.6, genism libraries, sklearn, scipy, pandas, word2vec and doc2vec technology. The article also describes a way to accelerate chatbot feedback and training using KD-Trees.

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Kovalenko Anna Vladimirovna
Doctor of Technical Sciences Associate Professor
Email: savanna-05@mail.ru

Kuban State University

Krasnodar, Russian Federation

Syusyura Daria Alekseevna

Kuban State University

Krasnodar, Russian Federation

Sharpan Maria Vladimirovna
Candidate of Physical and Mathematical Sciences Associate Professor

Krasnodar University of the Ministry of Internal Affairs of Russia

Krasnodar, Russian Federation

Keywords: neural networks, chatbot, word2vec technology, messengers, word embedding

For citation: Kovalenko A.V. Syusyura D.A. Sharpan M.V. Chatbot based on neural networks and word embedding to increase customer loyalty. Modeling, Optimization and Information Technology. 2022;10(2). Available from: https://moitvivt.ru/ru/journal/pdf?id=1110 DOI: 10.26102/2310-6018/2022.37.2.014 (In Russ).


Full text in PDF

Received 12.12.2021

Revised 29.04.2022

Accepted 25.05.2022

Published 30.05.2022