Building a growing knowledge base requires a systematic three-step methodology:
- Raw material input stageUpload all kinds of raw materials (PDF/PPT/audio recordings, etc.) in bulk through 'My Documents'. It is recommended to upload the materials according to the classification of 'Core Materials + Reference Materials', e.g., a researcher can upload academic papers and industry white papers at the same time.
- AI processing stage: Systematic and automatic implementationdeep semantic parsing, included:
- Create cross-document conceptual linkages (e.g., automatically recognize the same term in different reports)
- Extract key arguments and data support
- Generate traceable semantic indexes
- Knowledge Precipitation Stage: Manually mark high-value content in the 'Knowledge Base', and the system will optimize subsequent recommendation algorithms accordingly, forming a positive cycle where the more you use it, the more accurate it becomes.
The key tip is to initially upload at least 20 documents in the relevant field to provide enough 'learning samples' for the AI.
This answer comes from the articleHiStella: Creating a Personalized AI Co-Agent Intelligent Space》
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