PPNW: personalized pairwise novelty loss weighting for novel recommendation

Computer Science

• Simulation Mode 83%
• Accuracy 66%
• User 50%
• User Preference 16%
• Ranking Algorithm 16%
• Recommender Systems 16%
• Functions 16%
• Roles 16%

Psychology

• Novelty 100%
• Preference 33%
• Weight Loss 16%
• Assumptions 16%
• Biases 16%

Economics, Econometrics and Finance

• Loss 33%
• Robustness 16%
• Labour 16%
• Diversity 16%