한국어 기계독해 기반 법률계약서 리스크 예측 모델

• 영문명: Risk Prediction Model of Legal Contract Based on Korean Machine Reading Comprehension
• 발행기관: 한국IT서비스학회
• 저자명: 이치훈(Chi Hoon Lee) 노지우(Noh Ji Woo) 정재훈(Jae Hoon Jeong) 주경식(Kyung Sik Joo) 이동희(Dong Hee Lee)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제20권 제1호, 131~143쪽, 전체 13쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2021.02.28

영문 초록

Commercial transactions, one of the pillars of the capitalist economy, are occurring countless times every day, especially small and medium-sized businesses. However, small and medium-sized enterprises are bound to be the legal underdogs in contracts for commercial transactions and do not receive legal support for contracts for fair and legitimate commercial transactions. When subcontracting contracts are concluded among small and medium-sized enterprises, 58.2% of them do not apply standard contracts and sign contracts that have not undergone legal review. In order to support small and medium-sized enterprises fair and legitimate contracts, small and medium-sized enterprises can be protected from legal threats if they can reduce the risk of signing contracts by analyzing various risks in the contract and analyzing and informing them of toxic clauses and omitted contracts in advance. We propose a risk prediction model for the machine reading-based legal contract to minimize legal damage to small and medium-sized business owners in the legal blind spots. We have established our own set of legal questions and answers based on the legal data disclosed for the purpose of building a model specialized in legal contracts. Quantitative verification was carried out through indicators such as EM and F1 Score by applying pine tuning and hostile learning to pre-learned machine reading models. The highest F1 score was 87.93, with an EM value of 72.41.

목차

1. 서론

2. 이론적 배경

3. 선행연구

4. 법률계약서 리스크 분석을 위한 기계독해 모델 생성

5. 실험 및 결과

6. 결론

키워드

Machine Reading Comprehension(MRC) Risk Prediction Legal Contract Artificial Intelligence(AI) Machine Learning Legal Tech