FORMATION OF HIGHLY SPECIALIZED CHATBOTS FOR ADVANCED SEARCH
Andrii Yarovyi
Vinnytsia National Technical University, Department for Computer Science (Ukraine)
https://orcid.org/0000-0002-6668-2425
Dmytro Kudriavtsev
dmytro_k@vntu.edu.uaVinnytsia National Technical University, Department for Computer Science (Ukraine)
https://orcid.org/0000-0001-7116-7869
Abstract
In this research, the formation of highly specialized chatbots was presented. The influence of multi-threading subject areas search was noted. The use of related subject areas in chatbot text analysing was defined. The advantages of using multiple related subject areas are noted using the example of an intelligent chatbot.
Keywords:
text-processing, intelligent data analysis, chatbot, advanced searchReferences
Agarwal S., Rahul P., Neetu: New Text Detection Technique Using Machine Learning Architecture. Dwivedi S., Singh S., Tiwari M., Shrivastava A. (eds): Flexible Electronics for Electric Vehicles. Lecture Notes in Electrical Engineering 863. Springer, Singapore, 2023 [https://doi.org/10.1007/978-981-19-0588-9_1].
Google Scholar
Arkoudas K.: ChatGPT is no Stochastic Parrot. But it also Claims that 1 is Greater than 1. Philos. Technol. 36(54), 2023 [https://doi.org/10.1007/s13347-023-00619-6A].
Google Scholar
Cao Y., Xu G., Gao Y., Song C.: Application of natural language processing technology based on TensorFlow framework in text mining and discovery algorithm. IET Communications 17, 2022 [https://doi.org/10.1049/cmu2.12534].
Google Scholar
Chen W. et al.: Improved Recurrent Neural Networks for Text Classification and Dynamic Sylvester Equation Solving. Neural Process Lett 55, 2023, 8755–8784 [https://doi.org/10.1007/s11063-023-11176-6Raj].
Google Scholar
Greco C. M., Tagarelli A.: Bringing order into the realm of Transformer-based language models for artificial intelligence and law. Artif Intell Law 2023) [https://doi.org/10.1007/s10506-023-09374-7].
Google Scholar
Henrickson L., Meroño-Peñuela A.: Prompting meaning: a hermeneutic approach to optimising prompt engineering with ChatGPT. AI & Soc 2023 [https://doi.org/10.1007/s00146-023-01752-8].
Google Scholar
Joseph J. F. J., Nonsiri S., Monsakul A.: Keras and TensorFlow: A Hands-On Experience. Prakash K. B., Kannan R., Alexander S., Kanagachidambaresan G. R. (eds): Advanced Deep Learning for Engineers and Scientists. EAI/Springer Innovations in Communication and Computing. Springer, Cham. 2021 [https://doi.org/10.1007/978-3-030-66519-7_4].
Google Scholar
Karchi R. P., Hatture S. M., Tushar T. S., Prathibha B. N.: AI-Enabled Sustainable Development: An Intelligent Interactive Quotes Chatbot System Utilizing IoT and ML. Whig P., Silva N., Elngar A. A., Aneja N., Sharma P. (eds): Sustainable Development through Machine Learning, AI and IoT. ICSD 2023. Communications in Computer and Information Science 1939. Springer, Cham. [https://doi.org/10.1007/978-3-031-47055-4_17].
Google Scholar
Kvyetnyy R., Ivanchuk Y., Yarovyi A., Horobets Y.: Algorithm for Increasing the Stability Level of Cryptosystems. Selected Papers of the VIII International Scientific Conference “Information Technology and Implementation" – IT&I-2021, 293–301.
Google Scholar
Meyer J. G. et al.: ChatGPT and large language models in academia: opportunities and challenges. BioData Mining 16(20), 2023 [https://doi.org/10.1186/s13040-023-00339-9].
Google Scholar
Mondal B.: Best 25 Datasets for NLP Projects. Kaggle [https://www.kaggle.com/discussions/general/150720] (avaible 13.05.2020).
Google Scholar
Pallis George, Trihinas D., Tryfonos A., Dikaiakos M.: DevOps as a Service: Pushing the Boundaries of Microservice Adoption. IEEE Internet Computing 22, 2018, 65–71 [https://doi.org/10.1109/MIC.2018.032501519].
Google Scholar
Raj A., Jasmine K.: Building Microservices with Docker Compose. The International Journal of Analytical and Experimental Modal Analysis XIII, 2021, 1215.
Google Scholar
Siad S. M.: The Promise and Perils of Google's Bard for Scientific Research. AI. 2023 [https://doi.org/10.17613/yb4n-mc79].
Google Scholar
Thapa S., Adhikari S.: ChatGPT, Bard, and Large Language Models for Biomedical Research: Opportunities and Pitfalls. Ann Biomed Eng 51, 2023, 2647–2651 [https://doi.org/10.1007/s10439-023-03284-0].
Google Scholar
Yarovyi A. et al.: Information technology in creating intelligent chatbots. Proc. SPIE 11176, 2019, 1117627 [https://doi.org/10.1117/12.2537415].
Google Scholar
Yarovyi A., Kudriavtsev D.: Dictionary data structure for a text analysis task using cross-references. IEEE 17th International Conference on Computer Sciences and Information Technologies – CSIT, 2022, 61–64 [https://doi.org/10.1109/CSIT56902.2022.10000460].
Google Scholar
Yarovyi A., Kudriavtsev D.: Method of multi-purpose text analysis based on a combination of knowledge bases for intelligent chatbot. CEUR Workshop Proceedings 2870, 2021, 1238–1248.
Google Scholar
Authors
Andrii YarovyiVinnytsia National Technical University, Department for Computer Science Ukraine
https://orcid.org/0000-0002-6668-2425
Head of Department for Computer Science of Vinnytsia National Technical University (Ukraine).
Author of more than 100 technical articles (29 Scopus indexed articles),
5 monographs, 2 patents.
Authors
Dmytro Kudriavtsevdmytro_k@vntu.edu.ua
Vinnytsia National Technical University, Department for Computer Science Ukraine
https://orcid.org/0000-0001-7116-7869
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