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dc.contributor.authorNgo, Q. Hung-
dc.contributor.authorNguyen, D. Hien-
dc.contributor.authorLe, Khac Nhien An-
dc.descriptionLecture Notes in Networks and Systems (LNNS, volume 734); CITA: Conference on Information Technology and its Applications; pp: 25-36.vi_VN
dc.description.abstractToday, the legal document system is increasingly strict with different levels of influence and affects activities in many different fields. The increasing number of legal documents interwoven with each other also leads to difficulties in searching and applying in practice. The construction of knowledge maps that involve one or a group of legal documents is an effective approach to represent actual knowledge domains. A legal knowledge graph constructed from laws and legal documents can enable a number of applications, such as question answering, document similarity, and search. In this paper, we describe the process of building a system of knowledge maps for the Vietnamese legal system from the source of about 325,000 legal documents that span all fields of social life. This study also proposes an integrated ontology to represent the legal knowledge from legal documents. This model integrates the ontology of relational knowledge and the graph of key phrases and entities in the form of a concept graph. It can express the semantics of the content of a given legal document. In addition, this study also describes the process of building and exploiting natural language processing tools to build a VLegalKMaps system, which is a repository of Vietnamese legal knowledge maps. We also highlight open challenges in the realization of knowledge graphs in a technical legal system that enables this approach at scale.vi_VN
dc.publisherSpringer Naturevi_VN
dc.subjectKnowledge Mapvi_VN
dc.subjectLegal AIvi_VN
dc.subjectLegal Linked Datavi_VN
dc.subjectLegal Documentsvi_VN
dc.subjectKnowledge Engineeringvi_VN
dc.titleBuilding Legal Knowledge Map Repository with NLP Toolkitsvi_VN
dc.typeWorking Papervi_VN
Appears in Collections:CITA 2023 (International)

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