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China Terminology ›› 2023, Vol. 25 ›› Issue (4): 3-11.doi: 10.12339/j.issn.1673-8578.2023.04.001

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Construction of Terminology Semantic Knowledge Base Based on Conceptual Structure and Distributed Representation

WANG Peiyan(), LI Linna(), SHEN Sijia()   

  • Received:2023-02-06 Revised:2023-03-21 Online:2023-09-26 Published:2023-09-26

Abstract:

The construction of lexical semantic knowledge base is a basic task in natural language processing and plays an important role in various subtasks of natural language processing. This paper proposes an automatic generation method of term concept KDML representation for compound terms. The method is based on the hierarchical structure of concepts, uses distributed representation method to represent concepts and term definition text, and performs concept disambiguation according to the semantic distance between concepts and terms definition text. The method can learn the semantic roles between concepts through K-nearest neighbor algorithm, and generates term concept representation according to KDML syntax rules. Our experimental results showed that the accuracy rate of the first sememe was 96%, and the F1 values of the total sememe, semantic role and total triple were 91.92%, 78.9% and 73.41% respectively.

Key words: distributed representation, semantic disambiguation, HowNet, construction of terminology semantic knowledge base