LangChain과 속성 기반 감성 분석 모델을 활용한 시스템 개발에 대한 연구: 부동산 도메인을 중심으로

• 영문명: A Study on the Development of a System Using LangChain and an Aspect-Based Sentiment Analysis Model: Focusing on the Real Estate Domain
• 발행기관: 한국IT서비스학회
• 저자명: 이민주(Min Ju Lee) 전원표(Won Pyo Jeon)
• 간행물 정보: 『한국IT서비스학회지』제24권 제1호, 41~59쪽, 전체 19쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2025.02.28

국문 초록

This paper proposes a question-answering system for generating user-customized responses in the real estate domain by leveraging aspect-based sentiment analysis and the LangChain framework. In the real estate market, actual residence reviews related to apartments provide crucial information to potential buyers. However, the vast amount of text and the diverse aspects covered in each review present limitations in efficiently analyzing and understanding this information. To address this issue, we trained a model to analyze sentiments of apartment review data based on residential values that people focus on. Additionally, by combining the sentiment analysis model with Retrieval-Augmented Generation (RAG) technology, we developed a system that extracts information from various sources and generates reliable answers to queries. For this purpose, we constructed an apartment review dataset for aspect-based sentiment analysis and integrated the trained model with LangChain and a vector database to build the system. The proposed system not only presents actual residence reviews of apartment complexes by residential values but also provides helpful information by linking with external data.

목차

1. 서론

2. 이론적 배경

3. 제안 방법

4. 결론 및 향후 연구 방향

참고문헌

키워드

ABSA LangChain Language Model Vector Database RAG