Background to the issue
Most users face the problem of difficulty in managing information effectively after it is saved, Recall provides a systematic solution through AI automatic classification and knowledge graph technology.
Main Functional Applications
- automatic classification: The system automatically adds tags based on the semantics of the content
- knowledge map: Building a network of connections between content
- preserve intact: save webpage/video full content to maintain context
Specific operational guidelines
- Check the accuracy of auto-generated tags when saving content
- Manually add important associations through the Knowledge Graph interface
- Regularly use the search function to verify organizational effectiveness
- Multi-Platform Backup with Markdown Export
advanced skill
Create 3-5 major knowledge domain labels to allow the system to learn categorization preferences. Research scenarios can be set up with specialized labels such as 'theoretical framework' and 'experimental data'; workplace use can be set up with functional classifications such as 'industry dynamics' and 'competitor analysis ' and other functional categories.
Effectiveness evaluation
After 1-2 weeks of implementation, 90% content should be able to be quickly located with 1-2 clicks, and the correlation coverage of major knowledge areas should be 70% or higher.
This answer comes from the articleRecall: display information about your personal knowledge base when browsing the webThe
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