Research on Intelligent Retrieval Technology of Archival Information Based on Artificial Intelligence

Abstract

Archival information management faces the dual challenges of explosive data growth and low retrieval efficiency. This paper explores the application methods of artificial intelligence technology in the field of archival retrieval, analyzes how natural language processing,
knowledge graphs and other technologies improve retrieval accuracy, studies the optimization paths of multimodal information fusion and
intelligent algorithms, and constructs a retrieval system framework oriented toward practical applications. Research shows that intelligent
retrieval technology can effectively improve the limitations of keyword matching in traditional archival management, achieve accurate identification of user intent through semantic understanding, and provide technical support for the digital transformation of archives.