Skip to main content

Enhancing Event Selection with ChatGPT-Powered Chatbot Assistant: An Innovative Approach to Input Data Preparation

  • Conference paper
  • First Online:
Biologically Inspired Cognitive Architectures 2023 (BICA 2023)

Abstract

This article discusses the development of a chatbot assistant that helps users select theater and concert events from a website using ChatGPT. The chatbot uses natural language processing and machine learning algorithms to understand uses queries and provide relevant recommendations. We provide an approach for input data preparation that allows the model to use necessary information about events, so to use the context about them that wasn’t received during model training. The article also explores the benefits of using a chatbot for event selection and the potential for future improvements in chatbot technology. Overall, this chatbot provides a user-friendly and efficient way to discover events.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 279.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abu Shawar, B., Atwell, E.: Chatbots: are they really useful? J. Lang. Technol. Comput. Linguist. 22, 29–49 (2007)

    Article  Google Scholar 

  2. Brandtzaeg, P.B., Følstad, A.: Why people use chatbots. Internet Sci. 12, 377–392 (2017)

    Article  Google Scholar 

  3. Angelov, S., Lazarova, M.: E-Commerce Distributed Chatbot System. In: Proceedings of the 9th Balkan Conference on Informatics (2019)

    Google Scholar 

  4. Weizenbaum, J.: Eliza—a computer program for the study of natural language communication between man and Machine. Commun. ACM 9, 36–45 (1966)

    Article  Google Scholar 

  5. Li, Q., et al.: A survey on text classification: from traditional to deep learning. ACM Trans. Intell. Syst. Technol. 13, 1–41 (2022)

    Google Scholar 

  6. Mikolov, T., et al.: Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013)

  7. Bojanowski, P., Grave, E., Joulin, A., Mikolov, T.: Enriching word vectors with subword information. Trans. Assoc. Comput. Linguist. 5, 135–146 (2017)

    Article  Google Scholar 

  8. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014)

  9. Vaswani, A., et al.: Attention is all you need. Adv. Neural Inform. Process. Syst. 1, 30 (2017)

    Google Scholar 

  10. Devlin, J., et al.: Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)

  11. Radford, A., et al.: Improving language understanding by generative pre-training (2018)

    Google Scholar 

  12. Radford, A., et al.: Language models are unsupervised multitask learners. OpenAI Blog 1(8), 9 (2019)

    Google Scholar 

  13. Mann, B., et al.: Language models are few-shot learners. arXiv preprint arXiv:2005.14165 (2020)

  14. GPT-4 Technical Report. https://arxiv.org/pdf/2303.08774.pdf. Accessed 31 Aug 2023

  15. Malynov, A., Prokhorov, I.: Development of an AI recommender system to recommend concerts based on microservice architecture using collaborative and content-based filtering methods. In: Brain-Inspired Cognitive Architectures for Artificial Intelligence: BICA* AI 2020: Proceedings of the 11th Annual Meeting of the BICA Society 11. Springer International Publishing, New York (2021)

    Google Scholar 

  16. Malynov, A., Prokhorov, I.: Clustering of concert and theater events based on their description. Proced. Comput. Sci. 213, 673–679 (2022)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrey Malynov .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Malynov, A., Prokhorov, I. (2024). Enhancing Event Selection with ChatGPT-Powered Chatbot Assistant: An Innovative Approach to Input Data Preparation. In: Samsonovich, A.V., Liu, T. (eds) Biologically Inspired Cognitive Architectures 2023. BICA 2023. Studies in Computational Intelligence, vol 1130. Springer, Cham. https://doi.org/10.1007/978-3-031-50381-8_62

Download citation

Publish with us

Policies and ethics