• 대한전기학회
Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
  • COPE
  • kcse
  • 한국과학기술단체총연합회
  • 한국학술지인용색인
  • Scopus
  • crossref
  • orcid

References

1 
J. J. Park, “A development of chatbot for emotional stress recognition and management using NLP,” The Transactions of the Korean Institute of Electrical Engineers, vol. 67, no. 7, pp. 954-961, 2018.DOI:10.5370/KIEE.2018.67.7.954DOI
2 
C. N. Ramadhani, “Chatbots in pharmacy: A boon or a bane for patient care and pharmacy practice?,” Sciences of Pharmacy, vol. 2, no. 3, pp. 117-133, 2023.DOI:10.58920/sciphar02030001DOI
3 
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, A. Kaiser and I. Polosukhin, “Attention is all you need,” Advances in Neural Information Processing Systems, vol. 30, no. 1, pp. 5998-6008, 2017.DOI:10.48550/arXiv.1706.03762DOI
4 
Y. Xian, C. H. Lampert, B. Schiele and Z. Akata, “Zero-shot Learning - A comprehensive evaluation of the good, the bad and the ugly,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 9, pp. 2251-2265, 2019.DOI:10.1109/TPAMI.2018.2857768DOI
5 
O. Vinyals, C. Blundell, T. Lillicrap and D. Wierstra, “Matching networks for one shot learning,” Advances in Neural Information Processing Systems, vol. 29, pp. 3630-3638, 2016.DOI:10.48550/arXiv.1606.04080DOI
6 
J. Snell, K. Swersky and R. Zemel, “Prototypical networks for few-shot learning,” Advances in Neural Information Processing Systems, vol. 30, pp. 4077-4087, 2017.DOI:10.48550/arXiv.1703.05175DOI
7 
S. Gururangan, A. Marasović, S. Swayamdipta, K. Lo, I. Beltagy, D. Downey and N. A. Smith, “Don't stop pretraining: Adapt language models to domains and tasks,” Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp 8342-8360, 2020.DOI:10.18653/v1/2020.acl-main.740DOI
8 
I. K. M. Jais, A. R. Ismail and S. Q. Nisa, “Adam optimization algorithm for wide and deep neural network,” Knowledge Engineering and Data Science, vol. 2, no. 1, pp. 41-46, 2019.DOI:10.17977/um018v2i12019p41-46DOI
9 
Cheonsu Jeong, “Domain-specialized LLM: Financial fine-tuning and utilization method using Mistral 7B,” Journal of Intelligence and Information Systems, vol. 30, no. 1, pp. 93-120, 2024.DOI:10.13088/jiis.2024.30.1.093DOI
10 
P. Lewis, E. Perez, A. Piktus, F. Petroni, V. Karpukhin, N. Goyal, H. Küttler, M. Lewis, W.-T. Yih, T. Rocktäschel, S. Riedel and D. Kiela, “Retrieval-augmented generation for knowledge-intensive NLP tasks,” Advances in Neural Information Processing Systems, vol. 33, pp. 9459-9474, 2020.DOI:10.48550/arXiv.2005.11401DOI
11 
J. C. Kim, E. B. Cho and J. H. Chang, “Construction of Dataset for the 5 Major Violent Crimes Through Collection and Preprocessing of Judgment,” Journal of artificial intelligence convergence technology, vol. 5, no. 1, pp. 11-16, 2025.DOI:10.23374/jaict.2025.5.1.002DOI
12 
R. Karthick, “Context-Aware Topic Modeling and Intelligent Text Extraction Using Transformer‑Based Architectures,” Journal of Science Technology and Research, vol. 6, no. 1, pp. 1-13, 2025.DOI:10.2139/ssrn.5275391DOI
13 
S. E. Lee, H. Yoo, K. Chung, “Pose Pattern Mining Using Transformer for Motion Classification,” Applied Intelligence, vol. 54, no. 5, pp. 3841-3858, 2024.DOI:10.1007/s10489-024-05325-0DOI
14 
J.W. Baek, K. Chung, “Multi-context mining based graph neural network for predicting emerging health risk,” IEEE Access, vol. 11, pp. 15153-15163, 2023.DOI:10.1109/ACCESS.2023.3243722DOI
15 
S. M. Jo, “A Study on Technical Analysis of Efficient Recommendation Systems,” Journal of Artificial Intelligence Convergence Technology, vol. 5, no. 1, pp. 17-22, 2025.DOI:10.23374/jaict.2025.5.1.003DOI
16 
S. M. Jo, “A Study on Generalization Performance Analysis of Artificial Intelligence Data Learning Techniques,” Journal of Artificial Intelligence Convergence Technology, vol. 5, no. 2, pp. 55-60, 2025.DOI:10.23374/jaict.2025.5.2.001DOI