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China Terminology ›› 2023, Vol. 25 ›› Issue (3): 18-26.doi: 10.12339/j.issn.1673-8578.2023.03.003

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Graph Construction of Linguistic Term Knowledge Based on Neo4j

WANG Haoxue1(), WANG Xinglong2()   

  • Received:2022-09-12 Revised:2023-02-06 Online:2023-07-05 Published:2023-07-03

Abstract:

Taking the Chinese Languistic Terms as data source and using the Neo4j graph database, we adopt a top-down graph construction model, and integrate event theory and event evolutionary graph construction methods to generate linguistic terminology knowledge graphs. We hope to visualize the five types of attribute values within linguistic terms and nine types of relationships among term nodes, and provide a more reasonable disciplinary knowledge graph construction model. We also analyze some features of the linguistic terminology knowledge graph, and summarize and outlook the research on linguistic terminology knowledge graph.

Key words: event evolutionary graph, knowledge graph, linguistic term, subject term, Neo4j

CLC Number:  (术语学)