A novel context-aware recommender system based on a deep sequential learning approach (CReS)

Keyphrases

• Systems-based 100%
• Term Representation 100%
• Learning Approaches 100%
• Deep Sequential Model 100%
• Context-aware Recommender Systems 100%
• Contextual Information 66%
• Item Relationships 66%
• Hierarchical Relationship 66%
• Unified Framework 33%
• Sequential Behavior 33%
• User Interest 33%
• Low-rank 33%
• User Interaction 33%
• State-of-the-art Techniques 33%
• Influence Users 33%
• User Preference 33%
• Auxiliary Input 33%
• Residual Connection 33%
• Multi-grained 33%
• Accurate Recommendation 33%
• Interpretable Results 33%
• User Representation 33%
• Hierarchical Attention Network 33%
• Dynamic Preferences 33%
• Hierarchical Users 33%
• Multiple Granularity 33%
• Sequential Features 33%
• Sequence-aware 33%
• Contextual Types 33%
• Bi-directional GRU 33%
• Short-term Preference 33%
• GRU Network 33%
• Ranking Vector 33%
• Final Users 33%
• User Dynamics 33%

Computer Science

• Learning Approach 100%
• Recommender Systems 100%
• Sequential Learning 100%
• Unified Framework 50%
• User Interaction 50%
• Context Information 50%
• Contextual Information 50%
• User Preference 50%
• Granularity 50%
• Attention Hierarchical Network 50%
• User Representation 50%