太赫兹科学与电子信息学报2024，Vol.22Issue(5)：503-515,13.DOI:10.11805/TKYDA2023436
实体识别技术研究进展综述
Overview of the research progress in entity recognition technology
摘要
Abstract
Entity recognition technology,as an important step in constructing knowledge graphs,has been extensively applied in natural language processing applications such as semantic network,machine translation,and question answering systems.It plays a crucial role in promoting the practical application of natural language processing technology.According to the development process of entity recognition technology,the existing entity recognition methods are investigated in this paper.These methods can be classified as:early rule and dictionary based entity recognition methods,machine learning based entity recognition methods,and deep learning-based entity recognition methods.The core ideas,advantages and disadvantages,and representative models of each entity recognition method are summarized,especially the latest entity recognition methods based on Bi-directional Long Short-term Memory(BiLSTM)and Transformer.Additionally,the current mainstream datasets and evaluation criteria are introduced.Finally,facing the semantic requirements of future machine communication,we have summarized the challenges faced by entity recognition technology,and its future advancement in Internet of Things(IoT)business data is anticipated.关键词
实体识别/语义提取/深度学习/知识图谱Key words
entity recognition/semantic extraction/deep learning/knowledge graph分类
电子信息工程引用本文复制引用
马艺洁,赖海光,刘子威,杨楠,张更新..实体识别技术研究进展综述[J].太赫兹科学与电子信息学报,2024,22(5):503-515,13.基金项目
国家自然科学基金资助项目(U21A20450 （）
62271266) （）
江苏省前沿引领技术基础研究专项资助项目(BK20192002 （）
BK20212001) （）
