计算机工程与应用2024，Vol.60Issue(1)：15-27,13.DOI:10.3778/j.issn.1002-8331.2304-0398
中文命名实体识别研究综述
Survey of Chinese Named Entity Recognition Research
摘要
Abstract
Named entity recognition(NER)is one of the most fundamental tasks in natural language processing,and its main content is to identify the entity types and boundaries with specific meanings in natural language text.However,the data samples of Chinese named entity recognition(CNER)have problems such as blurred word boundaries,semantic diversity,blurred morphological features and small Chinese corpus content,which make it difficult to improve the perfor-mance of Chinese NER.In this paper,firstly,the dataset,annotation scheme and evaluation index of CNER are intro-duced.Secondly,according to the research process of CNER,CNER methods are classified into three categories:rule-based methods,statistical-based methods and deep learning-based methods,and the main models of CNER based on deep learning in the past five years are summarized.Finally,the research trends of CNER are discussed to provide some refer-ence for the proposal of new methods and future research directions.关键词
自然语言处理/中文命名实体识别/深度学习/预训练模型/机器学习Key words
natural language processing/Chinese named entity recognition(CNER)/deep learning/pre-training models/machine learning分类
信息技术与安全科学引用本文复制引用
赵继贵,钱育蓉,王魁,侯树祥,陈嘉颖..中文命名实体识别研究综述[J].计算机工程与应用,2024,60(1):15-27,13.基金项目
新疆维吾尔自治区自然科学基金(2021D01C083,2022D01C692) （2021D01C083,2022D01C692）
新疆维吾尔自治区科技厅国际合作项目(2020E01023) （2020E01023）
新疆维吾尔自治区科技计划青年科学基金(2022D01C83) （2022D01C83）
国家部委重大专项 （）
国家自然科学基金(62266043,61966035). （62266043,61966035）
