AI-enabled smart labeling system
Feeds.Fun builds a three-stage label processing pipeline: primary classifier identifies underlying topics, intermediate analyzer extracts entity relations, and advanced processor performs semantic deep parsing via Gemini/GPT. Test data shows its tagging accuracy for technology news reaches 921 TP3T, significantly higher than the 671 TP3T of the open source NLP tool.The system supports a user intervention mechanism, allowing manual correction of incorrect tags or addition of custom tags, forming a continuously optimized intelligent filtering network. Typical configuration examples include: 'financial fraud → -100 points', 'quantum computing → +50 points', realizing quantitative management of content value.
- Technology dependency: API endpoints for OpenAI/Gemini need to be configured
- Extensibility: Python plugin with support for user-defined label processors
- Fault tolerance mechanism: automatic switching to local keyword matching mode in case of network outages
This answer comes from the articleFeeds.Fun: RSS feeds with automatic tagging and filtering of newsThe
