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基于BERT的领域本体分类关系自动识别研究
Authors
刘巍
杨恒
王思丽
祝忠明
Publication date
16 July 2021
Publisher
Doi
Cite
Abstract
【目的/意义】实现对领域本体分类关系的自动学习识别,解决领域本体知识框架结构体系的自动化构建问题。【方法/过程】通过对领域本体分类关系自动识别的国内外研究现状及存在问题进行分析总结,以当前开源的先进的深度学习文本预训练模型BERT为基础,研究构建了基于BERT的领域本体分类关系自动识别模型,并以资源环境学科领域为例进行了实验研究和评估分析。【结果/结论】模型能够实现对领域本体分类关系的自动识别,识别方法和流程具有极大地通用性和可移植性,识别精度比传统方法有了较大提升。但由于受分类标注语料的质量限制,模型精度尚未达到峰值,有待进一步优化提升。</p
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National Science Library,Chinese Academy of Sciences
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oai:ir.las.ac.cn:12502/11264
Last time updated on 21/12/2020