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Design of a Question-Answering System based on RAG Model for Domestic Companies

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2024, 29(7), pp.81-88
  • DOI : 10.9708/jksci.2024.29.07.081
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : May 23, 2024
  • Accepted : July 16, 2024
  • Published : July 31, 2024

Gwang-Wu Yi 1 Soo Kyun Kim 1

1제주대학교

Accredited

ABSTRACT

Despite the rapid growth of the generative AI market and significant interest from domestic companies and institutions, concerns about the provision of inaccurate information and potential information leaks have emerged as major factors hindering the adoption of generative AI. To address these issues, this paper designs and implements a question-answering system based on the Retrieval-Augmented Generation (RAG) architecture. The proposed method constructs a knowledge database using Korean sentence embeddings and retrieves information relevant to queries through optimized searches, which is then provided to the generative language model. Additionally, it allows users to directly manage the knowledge database to efficiently update changing business information, and it is designed to operate in a private network to reduce the risk of corporate confidential information leakage. This study aims to serve as a useful reference for domestic companies seeking to adopt and utilize generative AI.

Citation status

* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.