In2Rec: Influence-based Interpretable Recommendation

Engineering

• Experimental Result 100%
• Convex Optimization Problem 100%
• Matrix Factorization 100%
• Mode Condition 100%
• Maximum a Posteriori 100%
• Generative Process 100%
• Tasks 100%
• Black Box 100%
• Learning Algorithm 100%
• Historical Data 100%

Computer Science

• Interpretability 100%
• Machine Learning 50%
• User Satisfaction 50%
• Optimization Problem 50%
• Recommender Systems 50%
• Graphical Model 50%
• Historical Data 50%
• Recommendation Accuracy 50%
• Convex Optimization 50%
• Experimental Result 50%
• Learning Algorithm 50%
• Matrix Factorization 50%
• Auxiliary Information 50%

Keyphrases

• Influence Mechanism 100%
• Interpretable Recommendation 100%
• Missing Ratings 33%
• Bayesian Graphical Models 33%
• Content Review 33%
• Factorization Model 33%
• Estimation Task 33%
• Persuasiveness 33%
• Predict Rating 33%
• Item Contents 33%