摘要
传统档案管理模式面临着海量数据处理能力不足、知识关联挖掘深度不够、服务形式单一等现实挑战。针对这些难点,文章深入研究人工智能生成内容(AIGC)技术在档案知识重组中的应用方法。文章首先从自然语言处理、知识图谱构建技术、多模态融合技术等底层技术层面分析AIGC特点,然后基于这些技术,提出AIGC技术在档案知识重组中的应用路径,以期为档案智能化管理提供创新方案,助力档案知识资源的深度开发与高效利用。
Traditional archives management faces practical challenges,including limited capacity for processing largescale data,insufficient depth in mining knowledge associations,and rigid service formats.To address these challenges,this paper explores the application of AI-generated content(AIGC)in archives knowledge reorganization.The paper first analyzes the characteristics of AIGC in terms of core enabling technologies,including natural language processing(NLP),knowledge graph construction,and multimodal fusion.Building on these technologies,it proposes a framework for applying AIGC to archives knowledge reorganization,offering an innovative approach to intelligent archival management and enabling the in-depth development and efficient utilization of archival knowledge.
作者
张红梅
Zhang Hongmei(Qingyang Highway Development Center of Gansu Province,Qingyang 745000,China)
出处
《办公自动化》
2025年第23期123-125,共3页
Office Informatization
关键词
人工智能生成内容(AIGC)技术
档案知识重组
自然语言处理技术
知识图谱
深度学习
artificial intelligence generated content(AIGC)technology
archives knowledge reorganization
natural language processing technology
knowledge graph
deep learning
