Search & Retrieval
Reranking
Adjust search result order using feedback signals and popularity metrics
Reranking is only available for enterprise customers, email info@mixpeek.com for a demo.
Ranking Types
Feedback Signals
- Click interactions
- View duration
- Skip actions
- Custom events
Popularity Metrics
- Historical engagement
- Recent interactions
- Time decay
- Confidence scores
Collaborative Filtering
- User similarities
- Item-based patterns
- Personalized scores
- Interaction history
Configuration
Interaction Recording
Common Use Cases
Implementation Flow
Best Practices
1
Choose Ranking Method
Start with basic feedback-based ranking before enabling collaborative filtering
2
Configure Weights
Balance between immediate feedback and collaborative patterns
3
Handle Cold Start
Fallback to popularity metrics for new users/items
4
Monitor Performance
Track relevance metrics and adjust weights accordingly
Limitations
Consider these constraints:
- Collaborative filtering requires sufficient interaction data
- Cold-start challenges for new users/items
- Processing overhead for large interaction datasets
- Memory requirements for similarity matrices
For detailed implementation examples, see the Interactions API Reference.
Was this page helpful?