Efficiency and accuracy improvement of document verification: automation and method analysis

This article introduces an automated document verification system based on computer and artificial intelligence technology. In response to the challenges faced by manual document verification in the digital age, the focus is on metadata comparison, document structure analysis, content feature extraction, and content vectorization. Through rigorous experimentation and validation, the system has demonstrated excellent accuracy and efficiency in classifying various document types (including Word documents, Excel spreadsheets, PDFs, images, videos, and audio recordings), achieving an average classification accuracy of 93%, demonstrating the robustness and scalability of the system, highlighting its adaptability in real-world validation scenarios across various industries, and providing an effective solution for organizations seeking efficient, accurate, and scalable document validation processes.