- Session-based Recommendations with Recurrent Neural Networks [ICLR 2016] [PDF] [code]
- Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks [RecSys 2017] [PDF] [code]
- Neural Attentive Session-based Recommendation [CIKM 2017] [PDF] [code]
- Sequential Recommendation with User Memory Networks [WSDM 2018] [PDF]
- STAMP: Short-Term Attention/Memory Priority Model for Session-based Recommendation [KDD 2018] [PDF] [code]
- Improving Sequential Recommendation with Knowledge-Enhanced Memory Networks [SIGIR 2018] [PDF] [code]
- Sequence-Aware Recommender Systems [ACM Computing Surveys 2018] [PDF] [code]
- BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer [CIKM 2019] [PDF] [code]
- Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks [PDF]
- RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-based Recommendation [AAAI 2019] [PDF] [code]
- Session-based Recommendation with Graph Neural Networks [AAAI 2019] [PDF] [code]
- A Collaborative Session-based Recommendation Approach with Parallel Memory Modules [SIGIR 2019] [PDF] [code]
- π-Net: A Parallel Information-sharing Network for Shared-account Cross-domain Sequential Recommendations [SIGIR 2019] [PDF] [code]
- Streaming Session-based Recommendation [KDD 2019] [PDF]
- A Survey on Session-based Recommender Systems [Arxiv 2019] [PDF]
- Empirical Analysis of Session-Based Recommendation Algorithms [Arxiv 2019] [PDF]
- Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations [Arxiv 2019] [PDF]
-
$S^3$ -Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization [CIKM 2020] [PDF] [code] - SSE-PT: Sequential Recommendation Via Personalized Transformer [RecSys 2020] [PDF] [code]
- Sequential Recommendation with Self-Attentive Multi-Adversarial Network [SIGIR 2020] [PDF]
- KERL: A Knowledge-Guided Reinforcement Learning Model for Sequential Recommendation [SIGIR 2020] [PDF] [code]
- Next-item Recommendation with Sequential Hypergraphs [SIGIR 2020] [PDF] [code]
- Self-Supervised Reinforcement Learning for Recommender Systems [SIGIR 2020] [PDF]
- Future Data Helps Training: Modeling Future Contexts for Session-based Recommendation [WWW 2020] [PDF] [code]
- Cross-domain recommendation without shared users or items by sharing latent vector distributions [AISTATS 2015] [PDF]
- Cross-Domain Recommendation: An Embedding and Mapping Approach [IJCAI 2017] [PDF] [code]
- Item Silk Road: Recommending Items from Information Domains to Social Users [SIGIR 2017] [PDF] [code]
- CoNet: Collaborative Cross Networks for Cross-Domain Recommendation [CIKM 2018] [PDF]
- A Deep Framework for Cross-Domain and Cross-System Recommendations [IJCAI 2018] [PDF]
- Domain-to-Domain Translation Model for Recommender System [Arxiv 2018] [PDF]
- Cross-Domain Recommendation via Preference Propagation GraphNet [CIKM 2019] [PDF] [code]
- Semi-Supervised Learning for Cross-Domain Recommendation to Cold-Start Users [CIKM 2019] [PDF]
- DTCDR A Framework for Dual-Target Cross-Domain Recommendation [CIKM 2019] [PDF]
- DARec: Deep Domain Adaptation for Cross-Domain Recommendation via Transferring Rating Patterns [IJCAI 2019] [PDF]
- Cross-domain Recommendation Without Sharing User-relevant Data [WWW 2019] [PDF]
- DDTCDR: Deep Dual Transfer Cross Domain Recommendation [WSDM 2020] [PDF] [code]
- CATN Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network [SIGIR 2020] [PDF] [code]
- Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation [SIGIR 2020] [PDF]
- Collaborative Fashion Recommendation: A Functional Tensor Factorization Approach [MM 2015] [PDF]
- VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback [AAAI 2016] [PDF] [code]
- Visually-Aware Fashion Recommendation and Design with Generative Image Models [ICDM 2017] [PDF] [code]
- Mining Fashion Outfit Composition Using an End-to-End Deep Learning Approach on Set Data [TMM 2017] [PDF]
- Learning Fashion Compatibility with Bidirectional LSTMs [MM 2017] [PDF] [code]
- NeuroStylist Neural Compatibility Modeling for Clothing Matching [MM 2017] [PDF]
- Neural Compatibility Modeling with Attentive Knowledge Distillation [SIGIR 2018] [PDF]
- Aesthetic-based Clothing Recommendation [WWW 2018] [PDF] [code]
- Personalized Fashion Recommendation with Visual Explanations based on Multimodal Attention Network [SIGIR 2019] [PDF] [code]
- Interpretable Fashion Matching with Rich Attributes [SIGIR 2019] [PDF]
- Prototype-guided Attribute-wise Interpretable Scheme for Clothing Matching [SIGIR 2019] [PDF]
- Dressing as a Whole Outfit Compatibility Learning Based on Node-wise Graph Neural Networks [WWW 2019] [PDF] [code]
- Improving Outfit Recommendation with Co-supervision of Fashion Generation [WWW 2019] [PDF] [code]
- An End-to-End Attention-Based Neural Model for Complementary Clothing Matching [TMM 2020] [PDF] [code]
- Hierarchical Fashion Graph Network for Personalised Outfit Recommendation [SIGIR 2020] [PDF] [code]
- FashionBERT Text and Image Matching with Adaptive Loss for Cross-modal Retrieval [SIGIR 2020] [PDF] [code]
- Explainable Outfit Recommendation with Joint Outfit Matching and Comment Generation [TKDE 2020] [PDF] [code]
- Explainable Recommendation via Multi-Task Learning in Opinionated Text Data [SIGIR 2018] [PDF] [code]
- TEM: Tree-enhanced Embedding Model for Explainable Recommendation [WWW 2018] [PDF]
- Explainable Reasoning over Knowledge Graphs for Recommendation [AAAI 2019] [PDF] [code]
- Reinforcement Knowledge Graph Reasoning for Explainable Recommendation [SIGIR 2019] [PDF] [code]
- A Capsule Network for Recommendation and Explaining What You Like and Dislike [SIGIR 2019] [PDF] [code]
- Jointly Learning Explainable Rules for Recommendation with Knowledge Graph [WWW 2019] [PDF] [code]
- Explainable Knowledge Graph-based Recommendation via Deep Reinforcement Learning [Arxiv 2019] [PDF]
- Explainable Recommender Systems via Resolving Learning Representations [CIKM 2020] [PDF]
- Fairness-Aware Explainable Recommendation over Knowledge Graphs [SIGIR 2020] [PDF] [code]
- Measuring Recommendation Explanation Quality: The Conflicting Goals of Explanations [SIGIR 2020] [PDF]
- Dual Learning for Explainable Recommendation: Towards Unifying User Preference Prediction and Review Generation [WWW 2020] [PDF]
- Explainable Recommendation: A Survey and New Perspectives [Foundations and Trends in Information Retrieval 2020] [PDF]
- Conversational Recommendation System with Unsupervised Learning [RecSys 2016] [PDF]
- Towards Conversational Search and Recommendation: System Ask, User Respond [CIKM 2018] [PDF] [code]
- Towards Deep Conversational Recommendations [NIPS 2018] [PDF]
- Conversational Recommender System [SIGIR 2018] [PDF]
- Towards Knowledge-Based Recommender Dialog System [EMNLP 2019] [PDF] [code]
- Estimation-Action-Reflection Towards Deep Interaction Between Conversational and Recommender Systems [WSDM 2020] [PDF] [code]
- What does BERT know about books, movies and music? Probing BERT for Conversational Recommendation [RecSys 2020] [PDF]
- Towards Conversational Recommendation over Multi-Type Dialogs [ACL 2020] [PDF]
- Neural Interactive Collaborative Filtering [SIGIR 2020] [PDF] [code]
- Towards Question-based Recommender Systems [SIGIR 2020] [PDF] [code]
- Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning [SIGIR 2020] [PDF] [code]
- Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-Start Users [Arxiv 2020] [PDF]
- A Survey on Conversational Recommender Systems [Arxiv 2020] [PDF]
- Meta-Learning Perspective on Cold-Start Recommendations for Items [NIPS 2017] [PDF]
- Federated Meta-Learning with Fast Convergence and Efficient Communication [Arxiv 2018] [PDF]
- Sequential Scenario-Specific Meta Learner for Online Recommendation [KDD 2019] [PDF] [code]
- MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation [KDD 2019] [PDF] [code]
- How to Retrain Recommender System? A Sequential Meta-Learning Method [SIGIR 2020] [PDF] [code]
- MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection [WWW 2020] [PDF]
- Meta Matrix Factorization for Federated Rating Predictions [SIGIR 2020] [PDF] [code]
- RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems [CIKM 2018] [PDF] [code]
- DKN: Deep Knowledge-Aware Network for News Recommendation [WWW 2018] [PDF] [code]
- Knowledge Graph Convolutional Networks for Recommender Systems [WWW 2019] [PDF] [code]
- KGAT: Knowledge Graph Attention Network for Recommendation [KDD 2019] [PDF] [code]
- Multi-modal Knowledge Graphs for Recommender Systems [CIKM 2020] [PDF]
- Jointly Non-Sampling Learning for Knowledge Graph Enhanced Recommendation [SIGIR 2020] [PDF] [code]
- Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs [SIGIR 2020] [PDF]
- Deep Matrix Factorization Models for Recommender Systems [IJCAI 2017] [PDF] [code]
- Neural Collaborative Filtering [WWW 2017] [PDF] [code]
- Collaborative Metric Learning [WWW 2017] [PDF] [code]
- Outer Product-based Neural Collaborative Filtering [IJCAI 2018] [PDF] [code]
- NeuRec: On Nonlinear Transformation for Personalized Ranking [IJACA 2018] [PDF] [code]
- Collaborative Memory Network for Recommendation Systems [SIGIR 2018] [PDF] [code]
- DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System [AAAI 2019] [PDF] [code]
- STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems [IJCAI 2019] [PDF] [code]
- Neural Graph Collaborative Filtering [SIGIR 2019] [PDF] [code]
- Graph neural networks for social recommendation [WWW 2019] [PDF] [code]
- Deep Learning Based Recommender System: A Survey and New Perspectives [ACM Computing Surveys 2019] [PDF]
- Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation [AAAI 2020] [PDF] [code]
- Disentangled Graph Collaborative Filtering [SIGIR 2020] [PDF] [code]