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Izvorni znanstveni članak
https://doi.org/10.17559/TV-20201119084338

A Knowledge Graph Construction Approach for Legal Domain

Biao Dong* ; Department of Law, Beijing Technology and Business University, No. 11 Fucheng Road, Beijing, China
Haoze Yu ; Department of Computer, Beijing Technology and Business University, No. 11 Fucheng Road, Beijing, China
Haisheng Li ; Department of Computer, Beijing Technology and Business University, No. 11 Fucheng Road, Beijing, China

Puni tekst: engleski, pdf (1 MB) str. 357-362 preuzimanja: 49* citiraj
APA 6th Edition
Dong*, B., Yu, H. i Li, H. (2021). A Knowledge Graph Construction Approach for Legal Domain. Tehnički vjesnik, 28 (2), 357-362. https://doi.org/10.17559/TV-20201119084338
MLA 8th Edition
Dong*, Biao, et al. "A Knowledge Graph Construction Approach for Legal Domain." Tehnički vjesnik, vol. 28, br. 2, 2021, str. 357-362. https://doi.org/10.17559/TV-20201119084338. Citirano 12.05.2021.
Chicago 17th Edition
Dong*, Biao, Haoze Yu i Haisheng Li. "A Knowledge Graph Construction Approach for Legal Domain." Tehnički vjesnik 28, br. 2 (2021): 357-362. https://doi.org/10.17559/TV-20201119084338
Harvard
Dong*, B., Yu, H., i Li, H. (2021). 'A Knowledge Graph Construction Approach for Legal Domain', Tehnički vjesnik, 28(2), str. 357-362. https://doi.org/10.17559/TV-20201119084338
Vancouver
Dong* B, Yu H, Li H. A Knowledge Graph Construction Approach for Legal Domain. Tehnički vjesnik [Internet]. 2021 [pristupljeno 12.05.2021.];28(2):357-362. https://doi.org/10.17559/TV-20201119084338
IEEE
B. Dong*, H. Yu i H. Li, "A Knowledge Graph Construction Approach for Legal Domain", Tehnički vjesnik, vol.28, br. 2, str. 357-362, 2021. [Online]. https://doi.org/10.17559/TV-20201119084338

Sažetak
Considering that the existing domain knowledge graphs have difficulty in updating data in a timely manner and cannot make use of knowledge sufficiently in the construction process, this paper proposes a legal domain knowledge graph construction approach based on 'China Judgments Online' in order to manage the cases' knowledge contained in it. The construction process is divided into two steps. First, we extract the classification relationships of the cases from structured data. Then, we obtain attribute knowledge of cases from semi-structured data and unstructured data through a relationship extraction model based on an improved cross-entropy loss function. The triples describing knowledge of cases are stored through Neo4j. The accuracy of the proposed approach is verified through experiments and we construct a legal domain knowledge graph which contains more than 4K classification relationships and 12K attribute knowledge to prove its validity.

Ključne riječi
China Judgments Online; Domain Knowledge Graph; Neo4j; Relationship Extraction

Hrčak ID: 255702

URI
https://hrcak.srce.hr/255702

Posjeta: 103 *