摘要
文章深入研究了人工智能技术在档案检索与分类中的具体应用方法,旨在提高档案管理的智能化水平。首先,通过自然语言处理技术,系统能够理解和分析档案中的文本信息,使档案检索更智能化;其次,通过训练模型,系统能够根据档案的特征进行自动学习并不断优化检索策略,以提高档案检索的效率。在档案分类方面,通过自动识别和分类图像,系统能够更好地整理和管理档案,提高了档案分类的精度和效率。同时,通过模拟人脑神经网络的方式,深度学习能够更好地处理大规模、复杂的档案数据,实现更细致、准确的分类。
This paper deeply studies the application methods of artificial intelligence technology in archives retrieval and classification,aiming at improving the intelligence level of archives management.Firstly,through natural language processing technology,the system can understand and analyze the text information in the archives,so as to make the file retrieval more intelligent.Secondly,by training the model,the system can automatically learn according to the characteristics of the file and continuously optimize the search strategy to improve the efficiency of the file search.In terms of file classification,by automatically identifying and classifying images,the system can better organize and manage files,and improve the accuracy and efficiency of file classification.At the same time,by simulating the human brain neural network,deep learning can better handle largescale and complex archival data and achieve more detailed and accurate classification goals.
作者
王浩
WANG Hao(Henan Sports Science and Technology Center(Henan Anti Doping Center),Zhengzhou 450000,China)
出处
《计算机应用文摘》
2024年第17期85-87,共3页
Chinese Journal of Computer Application
关键词
人工智能技术
档案检索
档案分类
自然语言处理技术
深度学习
artificial intelligence technology
archive retrieval
archive classification
natural language processing technology
deep learning
