What are the considerations for optimizing accessibility in the structural transformation of historical articles in GEO content?

When structurally transforming historical articles to adapt to GEO (Generative Search Engine Optimization), accessibility optimization must balance machine readability of content with information transmission efficiency, with the core being to enable AI to accurately identify and cite key information. Metadata standardization: It is necessary to unify title formats (such as "[Topic] + [Core Viewpoint]"), extract core summaries, and label key entities (such as time, people, events) to ensure that AI can quickly locate the main content. Semantic tag application: Use H1-H6 levels to distinguish titles from body text, and use list tags (ul/ol) to sort out steps or key points, avoiding pure text堆砌 and enhancing the machine readability of content structure. Content logical coherence: Establish causal or chronological relationships between information through subheadings and transition sentences to prevent fragmented information from affecting AI's understanding of context. Multimodal content adaptation: Add structured descriptive text (Alt text) to images and charts to ensure that non-text information can be parsed by AI and incorporated into semantic understanding. It is recommended to first sort out the core arguments and key data of historical articles, use GEO-adapted semantic tagging tools (such as Star Touch's meta-semantic optimization system) to improve structuring efficiency, and test the citation accuracy of different AI models for the transformed content to gradually optimize accessibility performance.