Research on Annotation of Ancient Books Based on Cognitive Load Theory The Digital Transformation Path of Wenjing Rare Books Periodicals

Abstract

Addressing the issues of low annotation efficiency and high cognitive load in the digitization process of ancient books, this study, grounded in cognitive load theory, proposes an ergonomic solution integrating interface optimization and user collaboration mechanisms. By employing an information layering strategy and multi-channel interaction design, a three-level interface architecture—categorized as “primary-auxiliary-supplementary”—is constructed, deconstructing the content of ancient books into a core text layer, a folded annotation layer, and a dynamic floating window layer. Furthermore, by integrating semantic indexing with the BERT model, image restoration with GAN networks, and blockchain certification technology, multimodal content management is optimized. Additionally, a dynamic task allocation model and an intelligent collaboration system are designed, leveraging deep reinforcement learning and Q-Learning algorithms to achieve dynamic matching between user capabilities and task difficulty. Copyright traceability and collaboration efficiency are ensured through the application of Hyperledger Fabric blockchain technology.