深度学习在医药领域命名实体识别中的研究进展

Research Progress in the Application of Deep Learning in Medical Named Entity Recognition

医药领域中文本作为一种主要的信息载体,其非结构化特征导致很难利用计算机直接进行批量分析。自然语言处理技术是自然语言与计算机语言之间转换的一种工具,近几年随着深度学习的发展在文本处理领域中有了广泛的应用,而命名实体识别作为自然语言处理的一个分支,在知识库构建、信息抽取等任务中发挥着重要的作用。针对命名实体识别在医药文本中的应用,介绍了当前主流的命名实体识别研究方法及主要数据来源,突出深度学习在医药领域实体识别应用中的优势,为该领域相关研究提供参考。

As a main carrier of information in medical area,texts can hardly be analyzed directly in bulk because of their unstructured formats.Natural language processing is a tool to convert the natural language into computer language,which has been widely applied with the development of deep learning in text processing.Named entity recognition,a subtask of natural language processing,plays an important role in knowledge base construction and information extraction.In regard to the application of named entity recognition in medical text analysis,this article introduces the mainstream methods and data sources to illustrate the advantages of deep learning in this area,so as to give more reference for researchers in the field.