• Journal of Service Research and Studies
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• v.13 no.3
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• pp.82-104
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• 2023

This study analyzes the effect of users' experiences using AI chatbot services on relationship quality and behavioral intention. For the study, a survey was conducted on users who experienced AI chatbot services, and the research hypothesis was verified by analyzing the final 299 copies of valid data. As a result of the analysis, it was confirmed that satisfaction and trust, which are the relationship quality dimensions of AI chatbot service, were formed in users through the cognitive experience, emotional experience, and relational experience. In addition, it was confirmed that satisfaction and trust have a positive effect on the intention to continue using and recommending AI chatbot services, which correspond to the level of consumers' behavioral intentions, respectively. In addition, in terms of relationship quality, it was significant in all paths of the road of behavior, but in satisfaction, the path coefficient of the road of continuous use of AI chatbot and recommended road was significantly higher than the path coefficient in trust. This study provided a theoretical foundation that the relationship with relationship quality that affects behavioral intention also affects AI chatbot services in the online environment, and it is significant in that it suggests that relationship quality is an important mediating factor in establishing long-term relationships with consumers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.251-253
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• 2018

As the prices of agricultural, fishery, and dairy products have been fluctuating due to recent instability on commodity prices, so consumers have been more inclined to make purchase without specific criteria by relying on marketing or their personal experiences and senses of market. The core function of this application is precisely and conveniently telling the consumption index to consumers who are waved by unstable commodity prices by helping users to easily understand the price index of agricultural, fishery, and dairy products in real time using public data. And, it also includes the AI Chatbot and voice recognition function, and meets the convenience of natural language processing and hands-free etc..

• Korea Information Processing Society Review
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• v.30 no.1
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• pp.15-25
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• 2023

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.423-424
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• 2019

인공지능 기술의 발전으로 딥러닝, 자연어처리 기술이 챗봇(채팅+로봇)에 적용되어 금융, 헬스케어, 여행, 방송 등의 분야를 중심으로 챗봇 시장이 확대되고 있다. 이러한 디지털 환경의 변화에 따라 전통문화 관련 개방 데이터를 활용한 전통문화 콘텐츠의 활성화 방안에 대해 살펴보고자 한다. 전통문화 소재는 영화, 드라마, 애니메이션 등의 소재로 활용 폭이 꾸준히 확대되고 있으나 현대적인 재창조의 폭넓은 대상이 되지는 못하고 있다. 팩트를 다루는 역사적 사실은 물론, 그 당시 살았던 사람들의 이야기 발굴에 대한 창작자들의 수요에 부응할 수 있는 체계적인 정보서비스로서의 전통문화 분야 인공지능(AI) 챗봇 서비스는 예비창작자와 일반인에게 창작의 유용한 가이드가 될 것으로 기대한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.105-112
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• 2024

In contemporary society, the expression of emotions and self-reflection are considered pivotal factors with a positive impact on stress management and mental well-being, thereby highlighting the significance of journaling. However, traditional journaling methods have posed challenges for many individuals due to constraints in terms of time and space. Recent rapid advancements in chatbot and emotion analysis technologies have garnered significant attention as essential tools to address these issues. This paper introduces an artificial intelligence chatbot that integrates the GPT-3 model and emotion analysis technology, detailing the development process of a system that automatically generates journals based on users' chat data. Through this system, users can engage in journaling more conveniently and efficiently, fostering a deeper understanding of their emotions and promoting positive emotional experiences.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.53-59
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• 2021

In this paper, we propose a BERGPT-chatbot, a domestic AI chatbot that can alleviate negative emotions based on text input such as 'Replika'. We made BERGPT-chatbot into a chatbot capable of mitigating negative emotions by pipelined two models, KR-BERT and KoGPT2-chatbot. We applied a creative method of giving emotions to unrefined everyday datasets through KR-BERT, and learning additional datasets through KoGPT2-chatbot. The development background of BERGPT-chatbot is as follows. Currently, the number of people with depression is increasing all over the world. This phenomenon is emerging as a more serious problem due to COVID-19, which causes people to increase long-term indoor living or limit interpersonal relationships. Overseas artificial intelligence chatbots aimed at relieving negative emotions or taking care of mental health care, have increased in use due to the pandemic. In Korea, Psychological diagnosis chatbots similar to those of overseas cases are being operated. However, as the domestic chatbot is a system that outputs a button-based answer rather than a text input-based answer, when compared to overseas chatbots, domestic chatbots remain at a low level of diagnosing human psychology. Therefore, we proposed a chatbot that helps mitigating negative emotions through BERGPT-chatbot. Finally, we compared BERGPT-chatbot and KoGPT2-chatbot through 'Perplexity', an internal evaluation metric for evaluating language models, and showed the superity of BERGPT-chatbot.