In modern information processing scenarios, semantic mining of documents such as PDF/Word is a recognized technical difficulty. The parsing engine of Geek Sidebar adopts a multimodal fusion architecture: the text flow processing module extracts paragraph-level features based on the improved BERT architecture; the format analyzer identifies structural elements such as headings and tables; special content such as mathematical formulas and flowcharts are processed by a dedicated detector.
On the workflow, after the user uploads the document, the system first performs optical character recognition (for scanned documents) and format normalization, and then launches a three-level analysis: primary extraction to generate the directory outline and keyword cloud; intermediate analysis to build the document knowledge graph; in-depth processing to support semantic queries, such as "what are the limitations of the experimental methodology". Test data show that it takes only 4.7 seconds to generate an abstract for a 10-page technical document, and the completeness of key information captured reaches 89%.
This function is especially suitable for legal contract review, academic paper reading and other professional scenarios. Combined with the split-screen browsing design, users can synchronize the viewing of the original text and AI parsing results to achieve truly efficient in-depth reading.
This answer comes from the articleGeek Sidebar: Bookmarks Cloud Synchronization & AI Smart Browsing AssistantThe
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