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There have been numerous efforts to provide legal information to the general public easily. Most of the existing legal information services are based on keyword-oriented legal ontology. However, this keyword-oriented ontology construction has a sense of disparity from the relationship between the laws used together in actual cases. To solve this problem, it is necessary to study which laws are actually used together in various judicial precedents. However, this is difficult to implement with the existing methods used in computer science or law. In our study, we analyzed this by using topological data analysis, which has recently attracted attention very promisingly in the field of data analysis. In this paper, we applied the the Mapper algorithm, which is one of the topological data analysis techniques, to visualize the relationships that laws form organically in actual precedents.
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참고문헌 (13)
참고문헌 신청
M Ester / 1996 / Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise / Knowledge Discovery and Data Mining 96(34):226~231
G Hinton / 2002 / Stochastic Neighbor Embedding / Neural Information Processing Sys-tems 15:833~840
전예슬 / 2020 / Topological Data Analysis 기법을 활용한 호텔 리뷰데이터의 감성 키워드 기반 호텔 관계망 구축 / 응용통계연구 33(1):75~86
J.H. Jeong / GitHub
김지현 / 2012 / 법령정보 검색을 위한 생활용어와 법률용어 간의 대응관계 탐색 방법론 / 지능정보연구 18(3):137~152
G Hinton / 2002 / Stochastic Neighbor Embedding / Neural Information Processing Sys-tems 15:833~840
전예슬 / 2020 / Topological Data Analysis 기법을 활용한 호텔 리뷰데이터의 감성 키워드 기반 호텔 관계망 구축 / 응용통계연구 33(1):75~86
J.H. Jeong / GitHub
김지현 / 2012 / 법령정보 검색을 위한 생활용어와 법률용어 간의 대응관계 탐색 방법론 / 지능정보연구 18(3):137~152
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