Будь ласка, використовуйте цей ідентифікатор, щоб цитувати або посилатися на цей матеріал:
http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/10944| Назва: | The Determination and Visualisation of Key Concepts Related to the Training of Chatbots |
| Автори: | Liashenko, Roman Семеріков, Сергій Олексійович Ляшенко, Роман Олегович |
| Ключові слова: | chatbot training natural language processing machine learning bibliometric analysis |
| Дата публікації: | 8-жов-2024 |
| Видавництво: | Springer, Cham |
| Бібліографічний опис: | Liashenko R. The Determination and Visualisation of Key Concepts Related to the Training of Chatbots / Roman Liashenko, Serhiy Semerikov // Information Technology for Education, Science, and Technics : Proceedings of ITEST 2024, Volume 2 / editors : Emil Faure, Yurii Tryus, Tero Vartiainen, Olena Danchenko, Maksym Bondarenko, Constantine Bazilo, Grygoriy Zaspa // Lecture Notes on Data Engineering and Communications Technologies. – Cham : Springer, 2024. – Vol. 222. – P. 111–126. – DOI : https://doi.org/10.1007/978-3-031-71804-5_8 |
| Короткий огляд (реферат): | This study aims to identify and visualize key concepts related to chatbot training through bibliometric analysis. The analysis of 549 sources from Scopus revealed a significant increase in publications from 2018, with a surge in 2023 likely driven by ChatGPT’s advent. We have identified four clusters of research areas. Those clusters are: (1) natural language processing; (2) application of natural language processing technologies in society; (3) application of machine learning for natural language processing; (4) chatbots in education and services. Central concepts were identified within each cluster. The results of our findings define natural language understanding, language modelling, controlled use of large language models in education, application of virtual assistants and diagnostic systems, and integration of chatbots into adaptive learning systems as the most prominent leading research directions. The same results offer implications for education, AI research, and organizational strategies for integrating conversational agents. Key concepts are possible to integrate into curriculum development and future research in natural language processing. |
| Опис: | Big Bot Makes Small Talk: A research summary of Facebook’s Generative BST chatbot, May 2020. https://www.deeplearning.ai/the-batch/big-bot-makes-small-talk/. Accessed 13 May 2024 Bot Comic: How Google’s Meena chatbot developed a sense of humor, February 2020. https://www.deeplearning.ai/the-batch/bot-comic/. Accessed 13 May 2024 Chatbots Disagree on Covid-19: Medical chatbots offered conflicting Covid advice, April 2020. https://www.deeplearning.ai/the-batch/chatbots-disagree-on-covid-19/. Accessed 13 May 2024 Language Models, Extended: Large language models grew more reliable and less biased in 2022, December 2022. https://www.deeplearning.ai/the-batch/language-models-grew-more-reliable-and-less-biased-in-2022/. Accessed 13 May 2024 Chatbots for Productivity: Microsoft extends Copilot to 365 and Windows, September 2023. https://www.deeplearning.ai/the-batch/microsoft-extends-copilot-365-windows/. Accessed 13 May 2024 China Chases Chatbots: Chinese tech companies race to cash in on ChatGPT fever, March 2023. https://www.deeplearning.ai/the-batch/chinese-tech-companies-race-to-cash-in-on-chatgpt-fever/. Accessed 13 May 2024 Cost Containment for Generative AI: Microsoft’s quest to reduce the size and cost of language models, October 2023. https://www.deeplearning.ai/the-batch/microsofts-quest-to-reduce-the-size-and-cost-of-language-models/. Accessed 13 May 2024 Search War! Google and Microsoft both announce AI-Powered search, February 2023. https://www.deeplearning.ai/the-batch/google-and-microsoft-both-announce-ai-powered-search/. Accessed 13 May 2024 What We Know — and Don’t Know — About Foundation Models: A new Stanford index to assess the transparency of leading AI models, November 2023. https://www.deeplearning.ai/the-batch/a-new-stanford-index-to-assess-the-transparency-of-leading-ai-models/. Accessed 13 May 2024 Centre for Science and Technology Studies, Leiden University, The Netherlands: VOSviewer - Visualizing scientific landscapes (2024). https://www.vosviewer.com/. Accessed 13 May 2024 DeepLearning.AI: Search | The Batch | AI News & Insights, December 2023. https://www.deeplearning.ai/search/. Accessed 13 May 2024 Elsevier B.V.: Scopus - Document search | Signed in (2023). https://www.scopus.com/search/form.uri?display=basic#basic. Accessed 13 May 2024 Fadieieva, L.O.: Adaptive learning concept selection: a bibliometric review of scholarly literature from 2011 to 2019. Educ. Dimens. 9, 136–148 (2023). https://doi.org/10.31812/ed.643 Hamaniuk, V.A.: The potential of large language models in language education. Educ. Dimens. 5, 208–210 (2021). https://doi.org/10.31812/ed.650 Mintii, M.M.: Exploring the landscape of STEM education and personnel training: a comprehensive systematic review. Educ. Dimens. 9, 149–172 (2023). https://doi.org/10.31812/ed.583 Ndibalema, P.M.: The growth of cyberbullying among youth in higher learning institutions: a bibliometric analysis. Educ. Dimens. 10, 143–166 (2024). https://doi.org/10.55056/ed.700 OpenAI: Introducing ChatGPT, November 2022. https://openai.com/blog/chatgpt. Accessed 13 May 2024 Riabko, A.V., Vakaliuk, T.A.: Physics on autopilot: exploring the use of an AI assistant for independent problem-solving practice. Educ. Technol. Q. 2024(1), 56–75 (2024). https://doi.org/10.55056/etq.671 Shabelnyk, T.V., Krivenko, S.V., Rotanova, N.Y., Diachenko, O.F., Tymofieieva, I.B., Kiv, A.E.: Integration of chatbots into the system of professional training of Masters. In: CTE Workshop Proceedings, vol. 8, pp. 212–220, March 2021. https://doi.org/10.55056/cte.233 Van Eck, N.J., Waltman, L.: VOSviewer Manual. Universiteit Leiden (2023). https://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.20.pdf. Accessed 13 May 2024 |
| URI (Уніфікований ідентифікатор ресурсу): | https://doi.org/10.1007/978-3-031-71804-5_8 https://link.springer.com/chapter/10.1007/978-3-031-71804-5_8 http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/10944 |
| ISBN: | 978-3-031-71803-8 978-3-031-71804-5 |
| Розташовується у зібраннях: | Кафедра інформатики та прикладної математики |
Файли цього матеріалу:
| Файл | Опис | Розмір | Формат | |
|---|---|---|---|---|
| ITEST_2024_vol_2-124-139_Liashenko_Semerikov.pdf | 1.37 MB | Adobe PDF | Переглянути/Відкрити |
Усі матеріали в архіві електронних ресурсів захищені авторським правом, всі права збережені.