| Title |
A Study on the Efficient Response to Architectural Civil Complaints Using Large Language Models(LLM) |
| Authors |
조상규(Cho, Sang-Kyu) ; 김신성(Kim, Shin-Sung) |
| DOI |
https://doi.org/10.5659/JAIK.2024.40.9.81 |
| Keywords |
Artificial Intelligence;Large Language Model;Architectural Law;Legal Interpretation System;Vector Database |
| Abstract |
This study addresses the complexity of architectural laws and regulations and their administrative burden, focusing on improving efficiency in
the interpretation and query-response processes using large-scale language models. The research centers around the development and
implementation of the SPARC (Semantic Processing for Architecture Regulation Compliance) engine, primarily utilizing data from inquiries
and complaints submitted to the Ministry of Land, Infrastructure, and Transport regarding architectural laws. This prototype system is
designed to augment reference information necessary for legal interpretation, and its effectiveness was validated through a quality assessment
of system responses to actual complaint data. The results show that the system achieved an accuracy rate of over 80% for general inquiry
complaints with clear conclusions and 70% to 100% for more complex cases requiring legal interpretation by the legislative affairs office.
This research represents the first attempt to apply AI in the field of regulatory administration, providing a critical technical and policy
foundation for the development and operation of AI-based systems for interpreting architectural regulations. |