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Could popularity bias reduce diversity in system's recommendations?
Could popularity bias reduce diversity in system's recommendations?
Recommendation systems often amplify what’s already popular, making it harder for niche or lesser-known options to be discovered. This can reduce diversity, personalization, and fairness in recommendations, limiting users’ exposure to a broader range of choices.
If you answered Yes then you are at risk
If you are not sure, then you might be at risk too
Recommendations
- Balance training data to include both popular and lesser-known items.
- Use bias-mitigation techniques like re-weighting or fairness-aware training.
- Apply post-processing methods like re-ranking to diversify recommendations.
- Regularly test for bias and adjust algorithms before deployment.