Sequential Recommender Systems: Challenges, Progress and Prospects
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Summary
The characteristics of SRSs are presented, and the key challenges in this research area are summarized and categorized, followed by the corresponding research progress consisting of the most recent and representative developments on this topic.
- Type
- article
- Published
- 2019-08-01
- Cited by
- 532
- References
- 27
- Access
- Open access
- OpenAlex
- https://openalex.org/W2965744319
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:199466417
Keywords
Recommender system, Popularity, Categorization, Key (lock), Collaborative filtering
References
- General factorization framework for context-aware recommendations
- Learning Hierarchical Representation Model for NextBasket Recommendation
- Personalized news recommendation with context trees
- Factorizing personalized Markov chains for next-basket recommendation
- Personalized Ranking Metric Embedding for Next New POI Recommendation
- Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations
- Training deep neural networks on imbalanced data sets
- Recurrent Recommender Networks
- Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks
- Translation-based Recommendation
- Diversifying Personalized Recommendation with User-session Context
- Inferring Implicit Rules by Learning Explicit and Hidden Item Dependency
- Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
- Sequential Recommendation with User Memory Networks
- Attention-Based Transactional Context Embedding for Next-Item Recommendation
- Improving Sequential Recommendation with Knowledge-Enhanced Memory Networks
- Sequential Recommender System based on Hierarchical Attention Networks
- Recommendation Through Mixtures of Heterogeneous Item Relationships
- Session-based Recommendation with Graph Neural Networks
- A Simple Convolutional Generative Network for Next Item Recommendation
Cited by
- A Survey on Session-based Recommender Systems
- Intention Nets: Psychology-Inspired User Choice Behavior Modeling for Next-Basket Prediction
- Diversified Interactive Recommendation with Implicit Feedback
- Intention Modeling from Ordered and Unordered Facets for Sequential Recommendation
- Graph Learning Approaches to Recommender Systems: A Review
- A Blockchain-enabled decentralized settlement model for IoT data exchange services
- Deep Conversational Recommender Systems: A New Frontier for Goal-Oriented Dialogue Systems
- Collaborative Filtering With Ranking-Based Priors on Unknown Ratings
- Hierarchical Attentive Transaction Embedding With Intra- and Inter-Transaction Dependencies for Next-Item Recommendation
- Global Context Enhanced Graph Neural Networks for Session-based Recommendation
- Sentiment-guided Sequential Recommendation
- Towards a Deep Attention-Based Sequential Recommender System
- Representation Learning With Multi-Level Attention for Activity Trajectory Similarity Computation
- Towards Cognitive Recommender Systems
- Contextual Bandits With Hidden Features to Online Recommendation via Sparse Interactions
- A Survey on Heterogeneous One-class Collaborative Filtering
- Next Basket Recommendation Model Based on Attribute-Aware Multi-Level Attention
- Semi-discrete Matrix Factorization
- Collaborative Generative Hashing for Marketing and Fast Cold-Start Recommendation
- Combination of individual and group patterns for time-sensitive purchase recommendation
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