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基于模式和投影学习的领域概念上下位关系自动识别研究
Authors
刘巍
杨恒
王思丽
祝忠明
Publication date
5 August 2020
Publisher
Doi
Abstract
[目的]实现对领域概念上下位关系的自动识别,以解决领域本体自动化构建中领域概念间语义关系的自动获取和确立问题。[方法]将传统无监督的基于模式的方法和当前先进的有监督的基于投影学习的方法有机结合起来应用于领域概念上下位关系自动识别,并进行了试验研究。[结果]能识别出领域概念的上位词集合,在医学领域的识别精度为0.88,通用领域的识别精度为0.83,在评估基准集BLESS上的平均精度为0.85。[局限]受句法歧义、语料集的质量等影响,模型精度尚未达到峰值,存在错误识别的情况。[结论]可发现同一概念词的不同意义的上位词,对低频词和命名实体也具有较好识别效果。未来可考虑从对高频顶层上位词进行适当减权、提升有监督语料集的质量等方面进行优化。 </p
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National Science Library,Chinese Academy of Sciences
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oai:ir.las.ac.cn:12502/11263
Last time updated on 21/12/2020