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Designing Conversational AI Services Using RAG-Based Loneliness Analysis for Koreans

RAG 기반 한국인 외로움 분석을 통한 대화형 인공지능 서비스 설계

  • 우승우 (강남대학교 인공지능학과) ;
  • 이민우 (강남대학교 인공지능학과) ;
  • 배성민 (강남대학교 데이터사이언스학과) ;
  • 송채빈 (강남대학교 데이터사이언스학과) ;
  • 서지훈 (강남대학교 데이터사이언스학과)
  • Received : 2024.08.15
  • Accepted : 2024.11.05
  • Published : 2024.11.30

Abstract

In this study, we designed an interactive AI service using the generative AI GPT-4o(Omni) model and RAG(Retrieval-Augmented Generation) to solve the problem of loneliness among the elderly. In this process, a questionnaire was created based on the Korean Loneliness Measurement Tool(KGLS) to measure the loneliness felt by the elderly in Korea, and a focus group interview was conducted with 10 real elderly people. Afterwards, we saved the PDF file on Korean loneliness in GPT-4o(Omni) to the Vector Store using RAG, and when the actual survey content was entered, we analysed the type of loneliness each user was experiencing and output prompts accordingly. Finally, this study designed an interactive A.I. service that can provide differentiated prompts according to the type of loneliness felt by the elderly, and aims to contribute to reducing loneliness and stress among the elderly.

본 연구는 노인들의 외로움 문제를 해결하기 위해 최근 주목받는 생성형 AI GPT-4o(옴니) 모델과 RAG(Retrieval-Augmented Generation)를 사용해서 대화형 인공지능 서비스를 설계하였다. 이 과정에서 한국 노인이 느끼는 외로움을 측정할 수 있도록 외로움 측정도구(KGLS)를 바탕으로 질문지를 만들었고, 실제 노인 10명을 대상으로 집단 심층면접(Focus Group Interview)을 진행하였다. 이후, GPT-4o(옴니)에 한국형 외로움에 관한 PDF 파일을 RAG를 사용해 벡터 스토어에 저장한 뒤, 실제 설문조사 내용을 입력받으면 사용자마다 겪고 있는 외로움 유형을 분석하고 그에 맞는 프롬프트를 출력하였다. 최종적으로 본 연구는 노인들이 느끼는 한국형 외로움 유형에 따라 차별화된 프롬프트를 제시할 수 있는 소통형 인공지능 서비스를 설계하였고, 노인들의 외로움과 스트레스 감소에 기여하고자 하였다.

Keywords

References

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