计算机应用与软件2024，Vol.41Issue(7)：42-48,7.DOI:10.3969/j.issn.1000-386x.2024.07.007
基于网络嵌入和预训练模型的义原预测
SEMEME PREDICTION BASED ON NETWORK EMBEDDING AND PRE-TRAINING MODEL
摘要
Abstract
Sememe is the core component of concept description in HowNet,and the predication of sememe description for new concepts is the key issue involved in automatic or semi-automatic expansion of HowNet.This paper proposes a sememe prediction method based on network embedding and the pre-training models.It realized the dynamic matching between the new concept and the candidate sememe by learning representation of the character-word-concept-sememe and their relationships in HowNet,and combining the pre-training language models to construct the partial"concept-sememe"relationship network.The predicted F1 value of the experimental results was 0.6237,which indicated that this method could solve the problem of semantic prediction of OOV words in HowNet more effectively.关键词
义原/预训练语言模型/网络嵌入Key words
Sememe/Pre-training language model/Network embedding分类
信息技术与安全科学引用本文复制引用
白宇,王之光,刘懿萱,蔡东风..基于网络嵌入和预训练模型的义原预测[J].计算机应用与软件,2024,41(7):42-48,7.基金项目
国家自然科学基金项目(U1908216). （U1908216）
