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

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

Datum izdavanja:

17.4.2021.

Posjeta: 2.575 *