人工智能技术在高校档案信息化建设中的应用研究

Research on the Application of Artificial Intelligence Technology in University Archives Informatization Construction

摘要: 人工智能技术的快速发展为高校档案信息化建设提供了新的技术路径与赋能机制。当前，高校档案工作正面临从传统管理模式向智能化、知识化、服务化转型的关键时期。本文聚焦自然语言处理、计算机视觉、知识图谱等核心人工智能技术，系统分析其在档案文本挖掘、图像语义解析、知识关联构建及智能服务等方面的应用场景。研究表明，人工智能技术能够显著提升档案信息化的自动化水平、知识组织能力与服务响应效率，推动档案资源从静态存储向动态知识服务转型。然而，技术落地仍面临数据标准化不足、领域知识建模滞后、安全审核机制不完善及复合型人才短缺等现实挑战。为此，高校需强化顶层设计，推进档案数据治理体系建设，优化开放审核机制，培养“档案 + AI”复合型人才，构建适应智能化发展的高校档案信息化生态。

Abstract: The rapid development of artificial intelligence technology has provided new technical paths and enabling mechanisms for the informatization construction of university archives. Currently, university archives are facing a critical period of transformation from traditional management models to intelligent, knowledge-based, and service-oriented systems. This paper focuses on core AI technologies such as natural language processing, computer vision, and knowledge graphs, systematically analyzing their application scenarios in archival text mining, image semantic analysis, knowledge association construction, and intelligent services. Research shows that AI technology can significantly improve the automation level, knowledge organization capability, and service response efficiency of archival informatization, promoting the transformation of archival resources from static storage to dynamic knowledge services. However, technological implementation still faces practical challenges such as insufficient data standardization, lagging domain knowledge modeling, imperfect security auditing mechanisms, and a shortage of interdisciplinary talents. Therefore, universities should strengthen top-level design, promote the construction of archival data governance systems, optimize open auditing mechanisms, cultivate “archives + AI” interdisciplinary talents, and build an intelligent university archives informatization ecosystem.