Leveraging user's preference and social circle for personalized recommendation via matrix factorization with sub-linear convergence rate

Computer Science

• Convergence Rate 100%
• User Preference 100%
• Experimental Result 50%
• Prediction Accuracy 50%
• Recommender System 50%
• Social Network 50%
• Contextual Information 50%
• User Experience 50%
• User Requirement 50%
• Preference Learning 50%
• Model Benchmark 50%
• Latent Dirichlet Allocation 50%
• Exponential Growth 50%