In this paper, we propose a conversational AI agent based on continual learning that can continuously learn and grow with new data over time. A continual learning-based conversational AI agent consists of three main components: Task manager, User attribute extraction, and Auto-growing knowledge graph. When a task manager finds new data during a conversation with a user, it creates a new task with previously learned knowledge. The user attribute extraction model extracts the user’s characteristics from the new task, and the auto-growing knowledge graph continuously learns the new external knowledge. Unlike the existing conversational AI agents that learned based on a limited dataset, our proposed method enables conversations based on continuous user attribute learning and knowledge learning. A conversational AI agent with continual learning technology can respond personally as conversations with users accumulate.
And it can respond to new knowledge continuously. This paper validate the possibility of our proposed method through experiments on performance changes in dialogue generation models over time.
@article{ART002927608}, author={Chae-Lim Park and So-Yeop Yoo and Ok-Ran Jeong}, title={A Study on Conversational AI Agent based on Continual Learning}, journal={Journal of The Korea Society of Computer and Information}, issn={1598-849X}, year={2023}, volume={28}, number={1}, pages={27-38}, doi={10.9708/jksci.2023.28.01.027}
TY - JOUR AU - Chae-Lim Park AU - So-Yeop Yoo AU - Ok-Ran Jeong TI - A Study on Conversational AI Agent based on Continual Learning JO - Journal of The Korea Society of Computer and Information PY - 2023 VL - 28 IS - 1 PB - The Korean Society Of Computer And Information SP - 27 EP - 38 SN - 1598-849X AB - In this paper, we propose a conversational AI agent based on continual learning that can continuously learn and grow with new data over time. A continual learning-based conversational AI agent consists of three main components: Task manager, User attribute extraction, and Auto-growing knowledge graph. When a task manager finds new data during a conversation with a user, it creates a new task with previously learned knowledge. The user attribute extraction model extracts the user’s characteristics from the new task, and the auto-growing knowledge graph continuously learns the new external knowledge. Unlike the existing conversational AI agents that learned based on a limited dataset, our proposed method enables conversations based on continuous user attribute learning and knowledge learning. A conversational AI agent with continual learning technology can respond personally as conversations with users accumulate.
And it can respond to new knowledge continuously. This paper validate the possibility of our proposed method through experiments on performance changes in dialogue generation models over time. KW - Dialogue system;Conversational AI agent;Continual learning;Chatbots;Knowledge graph DO - 10.9708/jksci.2023.28.01.027 ER -
Chae-Lim Park, So-Yeop Yoo and Ok-Ran Jeong. (2023). A Study on Conversational AI Agent based on Continual Learning. Journal of The Korea Society of Computer and Information, 28(1), 27-38.
Chae-Lim Park, So-Yeop Yoo and Ok-Ran Jeong. 2023, "A Study on Conversational AI Agent based on Continual Learning", Journal of The Korea Society of Computer and Information, vol.28, no.1 pp.27-38. Available from: doi:10.9708/jksci.2023.28.01.027
Chae-Lim Park, So-Yeop Yoo, Ok-Ran Jeong "A Study on Conversational AI Agent based on Continual Learning" Journal of The Korea Society of Computer and Information 28.1 pp.27-38 (2023) : 27.
Chae-Lim Park, So-Yeop Yoo, Ok-Ran Jeong. A Study on Conversational AI Agent based on Continual Learning. 2023; 28(1), 27-38. Available from: doi:10.9708/jksci.2023.28.01.027
Chae-Lim Park, So-Yeop Yoo and Ok-Ran Jeong. "A Study on Conversational AI Agent based on Continual Learning" Journal of The Korea Society of Computer and Information 28, no.1 (2023) : 27-38.doi: 10.9708/jksci.2023.28.01.027
Chae-Lim Park; So-Yeop Yoo; Ok-Ran Jeong. A Study on Conversational AI Agent based on Continual Learning. Journal of The Korea Society of Computer and Information, 28(1), 27-38. doi: 10.9708/jksci.2023.28.01.027
Chae-Lim Park; So-Yeop Yoo; Ok-Ran Jeong. A Study on Conversational AI Agent based on Continual Learning. Journal of The Korea Society of Computer and Information. 2023; 28(1) 27-38. doi: 10.9708/jksci.2023.28.01.027
Chae-Lim Park, So-Yeop Yoo, Ok-Ran Jeong. A Study on Conversational AI Agent based on Continual Learning. 2023; 28(1), 27-38. Available from: doi:10.9708/jksci.2023.28.01.027
Chae-Lim Park, So-Yeop Yoo and Ok-Ran Jeong. "A Study on Conversational AI Agent based on Continual Learning" Journal of The Korea Society of Computer and Information 28, no.1 (2023) : 27-38.doi: 10.9708/jksci.2023.28.01.027