Intelligent Sorting Algorithm Analysis
The system adopts a hybrid scoring strategy: base score is determined by news source authority (e.g., mainstream media +30 points), behavioral score is based on users' historical interactions (clicking/favoring +5 points), and rule-based score comes from labeling configuration (e.g., 'Breaking news x 2x weight'). Tests show the algorithm increases users' effective reading rate by 3.2x, while reducing information overload anxiety by 78%. A unique decay mechanism ensures that old news is automatically down-weighted, while urgent notifications are kept top-ranked via 'timeliness tags'. Enterprise users can export reading heat maps to analyze the distribution of their team's overall information preferences.
- Algorithmic transparency: real-time display of the composition of the score for each news item on the console
- Adaptive learning: automatically adjusting label weights based on rejection rates
- Scenario presets: built-in scoring templates for 'academic research', 'competitive monitoring', etc.
This answer comes from the articleFeeds.Fun: RSS feeds with automatic tagging and filtering of newsThe
