A hybrid of XGBoost and aspect-based review mining with attention neural network for user preference prediction

Keyphrases

• Aspect-oriented 100%
• Attention Mechanism 25%
• Attention Neural Network 100%
• Attention Weight 25%
• Attention-based 25%
• Bidirectional Gated Recurrent Unit (BiGRU) 25%
• Collaborative Filtering Method 50%
• Deep Learning Model 25%
• Gated Recurrent Unit 25%
• Gated Recurrent Unit Neural Network 25%
• Internet Development 25%
• Internet Users 25%
• Item-based 25%
• Latent Dirichlet Allocation 25%
• Latent Semantic 25%
• Prediction Accuracy 25%
• Prediction Method 50%
• Preference Rating 25%
• Rapid Development 25%
• Rating Prediction 50%
• Rating Score 25%
• Recommendation System 25%
• Review Mining 100%
• Semantic Aspect 25%
• Semantic Vectors 50%
• Social Platform 25%
• System Use 25%
• Two-stage Procedure 25%
• User Preference 50%
• User Preference Prediction 100%
• User Ratings 25%
• User Reviews 100%
• Word Attention 50%
• XGBoost 100%
• XGBoost Method 25%

Computer Science

• Attention (Machine Learning) 33%
• collaborative filtering algorithm 66%
• Deep Learning Model 33%
• Experimental Result 33%
• Extreme Gradient Boosting 100%
• Gated Recurrent Unit 66%
• Latent Dirichlet Allocation 33%
• Neural Network 100%
• Rapid Development 33%
• Semantic Review 33%
• Semantic Vector 66%
• Social Platform 33%
• User Preference 100%

Engineering

• Deep Learning Method 50%
• Dirichlet 50%
• Experimental Result 50%
• Filtration 100%
• Neural Unit 50%
• Rating Score 50%
• Recurrent 100%