Content quality control mechanisms
A three-layer calibration scheme is recommended to ensure the quality of the output:
- Input Optimization
Prioritize clearly structured source materials (e.g., PDFs with table of contents, videos with full captioning) and avoid scanned or speech-to-text content (error rate may be up to 15%) - parameterization
Use the Focus function to specify key sections (e.g., focus only on the "Market Analysis" section) prior to generation to improve accuracy through scope limitation. - output calibration
Use the Compare function to compare the raw text with the graph nodes, and the system will color-code anything with a confidence level lower than 80% for verification
Typical error handling: If you find that the timeline date is wrong, you can use Manual Mode to manually adjust the order of events; when the flowchart logic is abnormal, reconnect the nodes through the Relink function. It is recommended to keep 2-3 generated versions for important projects for cross-validation.
This answer comes from the articleMyLens AI: A Tool to Quickly Turn Text and Video into Interactive Visualization ChartsThe
May not be reproduced without permission:AI productivity tools " How do I ensure that the visualizations generated by MyLens AI are accurate?
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