News Recommendation Based on Collaborative Semantic Topic Models and Recommendation Adjustment

Keyphrases

• Ensemble Model 100%
• Semantic Topics 100%
• News Websites 100%
• News Articles 100%
• Model Modification 100%
• News Recommendation 100%
• Recommendation Adjustment 100%
• User Preference 50%
• Adjustment Mechanism 50%
• Experimental Performance Evaluation 50%
• Online Ratings 50%
• Recommendation Approach 50%
• Word Embedding 50%
• Preference-based 50%
• Latent Topics 50%
• Recommendation Quality 50%
• Novel Recommendation 50%
• Online News 50%
• Recommendation List 50%
• Latent Dirichlet Allocation 50%
• Online Assessment 50%
• Matrix Factorization 50%
• Real News 50%
• Offline Experiments 50%

Computer Science

• Experimental Result 100%
• User Preference 100%
• Latent Dirichlet Allocation 100%
• Matrix Factorization 100%
• Online Evaluation 100%
• Word Embedding 100%