ARTICLE A STUDY ON THE SIMILAR JUDGMENT OF KOREAN MEANING IN THE LEGAL FIELD USING DEEP LEARNING

저자

SUNGWON KIM, GWANGRYEOL PARK

인용

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초록
Keyword-oriented search methods are mainly used as data search methods, but this is not suitable as a search method in the legal field where professional terms are widely used. In response, this paper proposes an effective data search method in the legal field. We describe embedding methods optimized for determining similarities between sentences in the field of natural language processing of legal domains. After embedding legal sentences based on keywords using TF-IDF or semantic embedding using Universal Sentence Encoder, we propose an optimal way to search for data by combining BERT models to check similarities between sentences in the legal field.