人工智能背景下图书馆数据集成研究

Research on Data Integration in Libraries in the Context of Artificial Intelligence

在数字化时代,图书馆需要整合海量的数据资源,这些数据不仅形式和类型多样,并且有着不同来源,存在结构或格式上的差异。通过分析图书馆在多模态和异构数据集成时面临的诸多挑战,如数据异质性和复杂性、数据质量和标准化问题、技术集成和兼容性问题等,结合当前各种人工智能技术,如深度学习模型、图神经网络和自然语言处理等,探讨了针对各个问题的应对方法,旨在为图书馆提供高效的多模态和异构数据集成策略。

In the digital age,libraries need to integrate massive data resources,which have not only diverse forms and types,but also have different sources and differences in structures or formats.By analyzing the challenges faced by libraries in the integration of multi-modal and heterogeneous data,such as data heterogeneity and complexity,data quality and standardization,and technology integration and compatibility,and combined with current various artificial intelligence technologies such as the deep learning model,the graph neural network and natural language processing,this paper discusses copeing approaches to each problem,aiming to provide libraries with an efficient strategy for the integration of multi-modal and heterogeneous data.