Included Conferences: SIGIR 2020, SIGKDD 2020, RecSys 2020, CIKM 2020, AAAI 2021, WSDM 2021, WWW 2021, SIGIR 2021

• Task
  • Collaborative Filtering
  • Sequential/Session-based Recommendations
  • Knowledge-aware Recommendations
  • Feature Interactions
  • Conversational Recommender System
  • Social Recommendations
  • News Recommendation
  • Text-aware Recommendations
  • POI
  • Online Recommendations
  • Group Recommendation
  • Multi-task/Multi-behavior/Cross-domain Recommendations
  • Other Task
• Topic
  • Debias in Recommender System
  • Fairness in Recommender System
  • Attack in Recommender System
  • Explanation in Recommender System
  • Long-tail/Cold-start in Recommendations
  • Diversity in Recommendations
  • Evaluation
• Technique
  • Pre-training in Recommender System
  • Reinforcement Learning in Recommendations
  • Knowledge Distillation in Recommendations
  • NAS in Recommendations
  • Federated Learning in Recommendations
  • GNN in Recommendations
• Analysis
• Other

• LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. SIGIR 2020

• Deep Critiquing for VAE-based Recommender Systems. SIGIR 2020

• Neighbor Interaction Aware Graph Convolution Networks for Recommendation. SIGIR 2020

• A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks. KDD 2020

• Dual Channel Hypergraph Collaborative Filtering. KDD 2020

• Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. KDD 2020

• Content-Collaborative Disentanglement Representation Learning for Enhanced Recommendation. RecSys 2020

• Neural Collaborative Filtering vs. Matrix Factorization Revisited. RecSys 2020

• Bilateral Variational Autoencoder for Collaborative Filtering. WSDM 2021

• Learning User Representations with Hypercuboids for Recommender Systems. WSDM 2021

• Local Collaborative Autoencoders. WSDM 2021

• A Scalable, Adaptive and Sound Nonconvex Regularizer for Low-rank Matrix Completion. WWW 2021

• HGCF: Hyperbolic Graph Convolution Networks for Collaborative Filtering. WWW 2021

• High-dimensional Sparse Embeddings for Collaborative Filtering. WWW 2021

• Collaborative Filtering with Preferences Inferred from Brain Signals. WWW 2021

• Interest-aware Message-Passing GCN for Recommendation. WWW 2021

• Neural Collaborative Reasoning. WWW 2021

• Sinkhorn Collaborative Filtering. WWW 2021

• Disentangling User Interest and Conformity for Recommendation with Causal Embedding. WWW 2021

• Bootstrapping User and Item Representations for One-Class Collaborative Filtering. SIGIR 2021

• When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution. SIGIR 2021

• Neural Graph Matching based Collaborative Filtering. SIGIR 2021

• Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization. SIGIR 2021

• Sequential Recommendation with Self-attentive Multi-adversarial Network. SIGIR 2020

• KERL: A Knowledge-Guided Reinforcement Learning Model for Sequential Recommendation. SIGIR 2020

• Modeling Personalized Item Frequency Information for Next-basket Recommendation. SIGIR 2020

• Incorporating User Micro-behaviors and Item Knowledge into Multi-task Learning for Session-based Recommendation. SIGIR 2020

• GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation. SIGIR 2020

• Next-item Recommendation with Sequential Hypergraphs. SIGIR 2020

• A General Network Compression Framework for Sequential Recommender Systems. SIGIR 2020

• Make It a Chorus: Knowledge- and Time-aware Item Modeling for Sequential Recommendation. SIGIR 2020

• Global Context Enhanced Graph Neural Networks for Session-based Recommendation. SIGIR 2020

• Self-Supervised Reinforcement Learning for Recommender Systems. SIGIR 2020

• Time Matters: Sequential Recommendation with Complex Temporal Information. SIGIR 2020

• Controllable Multi-Interest Framework for Recommendation. KDD 2020

• Disentangled Self-Supervision in Sequential Recommenders. KDD 2020

• Handling Information Loss of Graph Neural Networks for Session-based Recommendation. KDD 2020

• Contextual and Sequential User Embeddings for Large-Scale Music Recommendation. RecSys 2020

• FISSA:Fusing Item Similarity Models with Self-Attention Networks for Sequential Recommendation. RecSys 2020

• From the lab to production: A case study of session-based recommendations in the home-improvement domain. RecSys 2020

• Recommending the Video to Watch Next: An Offline and Online Evaluation at YOUTV.de. RecSys 2020

• SSE-PT:Sequential Recommendation Via Personalized Transformer. RecSys 2020

• Improving End-to-End Sequential Recommendations with Intent-aware Diversification. CIKM 2020

• Quaternion-based self-Attentive Long Short-term User Preference Encoding for Recommendation. CIKM 2020

• Sequential Recommender via Time-aware Attentive Memory Network. CIKM 2020

• Star Graph Neural Networks for Session-based Recommendation. CIKM 2020

• Dynamic Memory Based Attention Network for Sequential Recommendation. AAAI 2021

• Noninvasive Self-Attention for Side Information Fusion in Sequential Recommendation. AAAI 2021

• Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. AAAI 2021

• An Efficient and Effective Framework for Session-based Social Recommendation. WSDM 2021

• Sparse-Interest Network for Sequential Recommendation. WSDM 2021

• Dynamic Embeddings for Interaction Prediction. WWW 2021

• Session-aware Linear Item-Item Models for Session-based Recommendation. WWW 2021

• RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation. WWW 2021

• Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation. WWW 2021

• Future-Aware Diverse Trends Framework for Recommendation. WWW 2021

• DeepRec: On-device Deep Learning for Privacy-Preserving Sequential Recommendation in Mobile Commerce. WWW 2021

• Linear-Time Self Attention with Codeword Histogram for Efficient Recommendation. WWW 2021

• Category-aware Collaborative Sequential Recommendation. SIGIR 2021

• Sequential Recommendation with Graph Convolutional Networks. SIGIR 2021

• Dual Attention Transfer in Session-based Recommendation with Multi Dimensional Integration. SIGIR 2021

• Unsupervised Proxy Selection for Session-based Recommender Systems. SIGIR 2021

• StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking. SIGIR 2021

• Counterfactual Data-Augmented Sequential Recommendation. SIGIR 2021

• CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation. SIGIR 2021

• The World is Binary: Contrastive Learning for Denoising Next Basket Recommendation. SIGIR 2021

• Motif-aware Sequential Recommendation. SIGIR 2021

• Lighter and Better: Low-Rank Decomposed Self-Attention Networks for Next-Item Recommendation. SIGIR 2021

• CKAN: Collaborative Knowledge-aware Attentive Network for Recommender Systems. SIGIR 2020

• Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. SIGIR 2020

• MVIN: Learning multiview items for recommendation. SIGIR 2020

• Jointly Non-Sampling Learning for Knowledge Graph Enhanced Recommendation. SIGIR 2020

• Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach. SIGIR 2020

• Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs. SIGIR 2020

• SimClusters Community-Based Representations for Heterogenous Recommendations at Twitter. KDD 2020

• Multi-modal Knowledge Graphs for Recommender Systems. CIKM 2020

• DisenHAN Disentangled Heterogeneous Graph Attention Network for Recommendation. CIKM 2020

• Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network. CIKM 2020

• TGCN Tag Graph Convolutional Network for Tag-Aware Recommendation. CIKM 2020

• Knowledge-Enhanced Top-K Recommendation in Poincaré Ball. AAAI 2021

• Graph Heterogeneous Multi-Relational Recommendation. AAAI 2021

• Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation. AAAI 2021

• Alleviating Cold-Start Problems in Recommendation through Pseudo-Labelling over Knowledge Graph. WSDM2021

• Decomposed Collaborative Filtering Modeling Explicit and Implicit Factors For Recommender Systems. WSDM 2021

• Temporal Meta-path Guided Explainable Recommendation. WSDM 2021

• Learning Intents behind Interactions with Knowledge Graph for Recommendation. WWW 2021

• Detecting Beneficial Feature Interactions for Recommender Systems. AAAI 2021

• DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving. WSDM 2021

• Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction. WSDM 2021

• FM^2: Field-matrixed Factorization Machines for CTR Prediction. WWW 2021

• Towards Question-based Recommender Systems. SIGIR 2020

• Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion. KDD 2020

• Interactive Path Reasoning on Graph for Conversational Recommendation. KDD 2020

• A Ranking Optimization Approach to Latent Linear Critiquing for Conversational Recommender Systems. RecSys 2020

• What does BERT know about books, movies and music： Probing BERT for Conversational Recommendation. RecSys 2020

• Adapting User Preference to Online Feedback in Multi-round Conversational Recommendation. WSDM 2021

• A Workflow Analysis of Context-driven Conversational Recommendation. WWW 2021

• Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning. SIGIR 2021

• Learning to Ask Appropriate Questions in Conversational Recommendation. SIGIR 2021

• Comparison-based Conversational Recommender System with Relative Bandit Feedback. SIGIR 2021

• Partial Relationship Aware Influence Diffusion via a Multi-channel Encoding Scheme for Social Recommendation. CIKM 2020

• Random Walks with Erasure: Diversifying Personalized Recommendations on Social and Information Networks. WWW 2021

• Dual Side Deep Context-aware Modulation for Social Recommendation. WWW 2021

• Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. WWW 2021

• KRED:Knowledge-Aware Document Representation for News Recommendations. RecSys 2020

• News Recommendation with Topic-Enriched Knowledge Graphs. CIKM 2020

• The Interaction between Political Typology and Filter Bubbles in News Recommendation Algorithms. WWW 2021

• Personalized News Recommendation with Knowledge-aware News Interactions. SIGIR 2021

• Joint Knowledge Pruning and Recurrent Graph Convolution for News Recommendation. SIGIR 2021

• TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations. RecSys 2020

• Set-Sequence-Graph A Multi-View Approach Towards Exploiting Reviews for Recommendation. CIKM 2020

• TPR: Text-aware Preference Ranking for Recommender Systems. CIKM 2020

• Leveraging Review Properties for Effective Recommendation. WWW 2021

• HME: A Hyperbolic Metric Embedding Approach for Next-POI Recommendation. SIGIR 2020

• Spatial Object Recommendation with Hints: When Spatial Granularity Matters. SIGIR 2020

• Geography-Aware Sequential Location Recommendation. KDD 2020

• Learning Graph-Based Geographical Latent Representation for Point-of-Interest Recommendation. CIKM 2020

• STP-UDGAT Spatial-Temporal-Preference User Dimensional Graph Attention Network for Next POI Recommendation. CIKM 2020

• STAN: Spatio-Temporal Attention Network for next Point-of-Interest Recommendation. WWW 2021

• Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. WWW 2021

• Gemini: A novel and universal heterogeneous graph information fusing framework for online recommendations. KDD 2020

• Maximizing Cumulative User Engagement in Sequential Recommendation An Online Optimization Perspective. KDD 2020

• Exploring Clustering of Bandits for Online Recommendation System. RecSys 2020

• Contextual User Browsing Bandits for Large-Scale Online Mobile Recommendation. RecSys 2020

• A Hybrid Bandit Framework for Diversified Recommendation. AAAI 2021

• GAME: Learning Graphical and Attentive Multi-view Embeddings for Occasional Group Recommendation. SIGIR 2020

• GroupIM: A Mutual Information Maximizing Framework for Neural Group Recommendation. SIGIR 2020

• Group-Aware Long- and Short-Term Graph Representation Learning for Sequential Group Recommendation. SIGIR 2020

• Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation. SIGIR 2020

• CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network. SIGIR 2020

• Multi-behavior Recommendation with Graph Convolution Networks. SIGIR 2020

• Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation. SIGIR 2020

• Web-to-Voice Transfer for Product Recommendation on Voice. SIGIR 2020

• Jointly Learning to Recommend and Advertise. KDD 2020

• Progressive Layered Extraction (PLE) A Novel Multi-Task Learning (MTL) Model for Personalized Recommendations. RecSys 2020

• Whole-Chain Recommendations. CIKM 2020

• Personalized Approximate Pareto-Efficient Recommendation. WWW 2021

• Federated Collaborative Transfer for Cross-Domain Recommendation. SIGIR 2021

• Learning Domain Semantics and Cross-Domain Correlations for Paper Recommendation. SIGIR 2021

• Graph Meta Network for Multi-Behavior Recommendation with Interaction Heterogeneity and Diversity. SIGIR 2021

• Hierarchical Fashion Graph Network for Personalized Outfit Recommendation. SIGIR 2020

• Octopus: Comprehensive and Elastic User Representation for the Generation of Recommendation Candidates. SIGIR 2020

• Goal-driven Command Recommendations for Analysts. RecSys 2020

• MultiRec: A Multi-Relational Approach for Unique Item Recommendation in Auction Systems. RecSys 2020

• PURS: Personalized Unexpected Recommender System for Improving User Satisfaction. RecSys 2020

• RecSeats: A Hybrid Convolutional Neural Network Choice Model for Seat Recommendations at Reserved Seating Venues. RecSys 2020

• Live Multi-Streaming and Donation Recommendations via Coupled Donation-Response Tensor Factorization. CIKM 2020

• Learning to Recommend from Sparse Data via Generative User Feedback. AAAI 2021

• Real-time Relevant Recommendation Suggestion. WSDM 2021

• Heterogeneous Graph Augmented Multi-Scenario Sharing Recommendation with Tree-Guided Expert Networks. WSDM 2021

• FINN: Feedback Interactive Neural Network for Intent Recommendation. WWW 2021

• Drug Package Recommendation via Interaction-aware Graph Induction. WWW 2021

• Large-scale Comb-K Recommendation. WWW 2021

• Variation Control and Evaluation for Generative Slate Recommendations. WWW 2021

• Diversified Recommendation Through Similarity-Guided Graph Neural Networks. WWW 2021

• Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue. SIGIR 2021

• UGRec: Modeling Directed and Undirected Relations for Recommendation. SIGIR 2021

• Learning Recommender Systems with Implicit Feedback via Soft Target Enhancement. SIGIR 2021

• PreSizE: Predicting Size in E-Commerce using Transformers. SIGIR 2021

• Path-based Deep Network for Candidate Item Matching in Recommenders. SIGIR 2021

• A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images. SIGIR 2021

• A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data. SIGIR 2020

• Measuring and Mitigating Item Under-Recommendation Bias in Personalized Ranking Systems. SIGIR 2020

• Attribute-based Propensity for Unbiased Learning in Recommender Systems Algorithm and Case Studies. KDD 2020

• Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions. KDD 2020

• Debiasing Item-to-Item Recommendations With Small Annotated Datasets. RecSys 2020

• Keeping Dataset Biases out of the Simulation : A Debiased Simulator for Reinforcement Learning based Recommender Systems. RecSys 2020

• Unbiased Ad Click Prediction for Position-aware Advertising Systems. RecSys 2020

• Unbiased Learning for the Causal Effect of Recommendation. RecSys 2020

• E-commerce Recommendation with Weighted Expected Utility. CIKM 2020

• Popularity-Opportunity Bias in Collaborative Filtering. WSDM 2021

• Combating Selection Biases in Recommender Systems with a Few Unbiased Ratings. WSDM 2021

• Leave No User Behind Towards Improving the Utility of Recommender Systems for Non-mainstream Users. WSDM 2021

• Non-Clicks Mean Irrelevant Propensity Ratio Scoring As a Correction. WSDM 2021

• Diverse User Preference Elicitation with Multi-Armed Bandits. WSDM 2021

• Unbiased Learning to Rank in Feeds Recommendation. WSDM 2021

• Cross-Positional Attention for Debiasing Clicks. WWW 2021

• Debiasing Career Recommendations with Neural Fair Collaborative Filtering. WWW 2021

• AutoDebias: Learning to Debias for Recommendation. SIGIR 2021

• Mitigating Sentiment Bias for Recommender Systems. SIGIR 2021

• Causal Intervention for Leveraging Popularity Bias in Recommendation. SIGIR 2021

• Enhanced Doubly Robust Learning for Debiasing Post-Click Conversion Rate Estimation. SIGIR 2021

• Fairness-Aware Explainable Recommendation over Knowledge Graphs. SIGIR 2020

• Ensuring Fairness in Group Recommendations by Rank-Sensitive Balancing of Relevance. RecSys 2020

• Fairness-Aware News Recommendation with Decomposed Adversarial Learning. AAAI 2021 news

• Practical Compositional Fairness Understanding Fairness in Multi-Component Recommender Systems. WSDM 2021

• Towards Long-term Fairness in Recommendation. WSDM 2021

• Learning Fair Representations for Recommendation: A Graph-based Perspective. WWW 2021

• User-oriented Group Fairness In Recommender Systems. WWW 2021

• Personalized Counterfactual Fairness in Recommendation. SIGIR 2021

• TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers. SIGIR 2021

• Fairness among New Items in Cold Start Recommender Systems. SIGIR 2021

• Revisiting Adversarially Learned Injection Attacks Against Recommender Systems. RecSys 2020

• Attacking Recommender Systems with Augmented User Profiles. CIKM 2020

• A Black-Box Attack Model for Visually-Aware Recommenders. WSDM 2021

• Denoising Implicit Feedback for Recommendation. WSDM 2021

• Adversarial Item Promotion: Vulnerabilities at the Core of Top-N Recommenders that Use Images to Address Cold Start. WWW 2021

• Graph Embedding for Recommendation against Attribute Inference Attacks. WWW 2021

• Fight Fire with Fire: Towards Robust Recommender Systems via Adversarial Poisoning Training. SIGIR 2021

• Try This Instead: Personalized and Interpretable Substitute Recommendation. KDD 2020

• CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation. CIKM 2020

• Explainable Recommender Systems via Resolving Learning Representations. CIKM 2020

• Generate Neural Template Explanations for Recommendation. CIKM 2020

• Explainable Recommendation with Comparative Constraints on Product Aspects. WSDM 2021

• Explanation as a Defense of Recommendation. WSDM 2021

• EX^3: Explainable Product Set Recommendation for Comparison Shopping. WWW 2021

• Learning from User Feedback on Explanations to Improve Recommender Models. WWW 2021

• On Interpretation and Measurement of Soft Attributes for Recommendation. SIGIR 2021

• ReXPlug: Explainable Recommendation using Plug-and-Play Language Model. SIGIR 2021

• User-Centric Path Reasoning towards Explainable Recommendation. SIGIR 2021

• Content-aware Neural Hashing for Cold-start Recommendation. SIGIR 2020

• MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation. KDD 2020

• Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling. KDD 2020

• Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation. KDD 2020

• Cold-Start Sequential Recommendation via Meta Learner. AAAI 2021

• Personalized Adaptive Meta Learning for Cold-start User Preference Prediction. AAAI 2021

• Task-adaptive Neural Process for User Cold-Start Recommendation. WWW 2021

• A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. WWW 2021

• Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction. SIGIR 2021

• FORM: Follow the Online Regularized Meta-Leader for Cold-Start Recommendation. SIGIR 2021

• Privileged Graph Distillation for Cold-start Recommendation. SIGIR 2021

• Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks. SIGIR 2021

• Fairness among New Items in Cold Start Recommender Systems. SIGIR 2021

• Fast Greedy MAP Inference for Determinantal Point Process to Improve Recommendation Diversity. NIPS 2018. PDF

• PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation. IJCAI 2019. PDF

• Sequential and Diverse Recommendation with Long Tail. IJCAI 2019. PDF

• Diversified Interactive Recommendation with Implicit Feedback. AAAI 2020. PDF

• ART (Attractive Recommendation Tailor): How the Diversity of Product Recommendations Affects Customer Purchase Preference in Fashion Industry. CIKM 2020. PDF

• A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks. KDD 2020. PDF

• Enhancing Recommendation Diversity using Determinantal Point Processes on Knowledge Graphs. SIGIR 2020. PDF

• A Hybrid Bandit Framework for Diversified Recommendation. AAAI 2021. PDF

• On the Diversity and Explainability of Recommender Systems: A Practical Framework for Enterprise App Recommendation. CIKM 2021. PDF

• P-Companion: A Principled Framework for Diversified Complementary Product Recommendation. CIKM 2021. PDF

• Sliding Spectrum Decomposition for Diversified Recommendation. KDD 2021. PDF

• Enhancing Domain-Level and User-Level Adaptivity in Diversified Recommendation. SIGIR 2021. PDF

• Dynamic Graph Construction for Improving Diversity of Recommendation. RecSys 2021. PDF

• Towards Unified Metrics for Accuracy and Diversity for Recommender Systems. RecSys 2021. PDF

• DGCN: Diversified Recommendation with Graph Convolutional Networks. WWW 2021. PDF

• Future-Aware Diverse Trends Framework for Recommendation. WWW 2021. PDF

• Random Walks with Erasure: Diversifying Personalized Recommendations on Social and Information Networks. WWW 2021. PDF

• Measuring Recommendation Explanation Quality: The Conflicting Goals of Explanations. SIGIR 2020

• Evaluating Conversational Recommender Systems via User Simulation. KDD 2020

• On Sampled Metrics for Item Recommendation. KDD 2020

• On Sampling Top-K Recommendation Evaluation. KDD 2020

• Are We Evaluating Rigorously： Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison. RecSys 2020

• On Target Item Sampling in Offline Recommender System Evaluation. RecSys 2020

• Standing in Your Shoes: External Assessments for Personalized Recommender Systems. SIGIR 2021

• S^3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization. CIKM 2020

• Self-supervised Learning for Large-scale Item Recommendations. arXiv 2020

• U-BERT Pre-Training User Representations for Improved Recommendation. AAAI 2021

• Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation. WSDM 2021

• Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer. SIGIR 2021

• Self-supervised Graph Learning for Recommendation. SIGIR 2021

• Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. AAAI 2021

• Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. WWW 2021

• Pre-training Graph Transformer with Multimodal Side Information for Recommendation. ACM MM2021

• SelfCF: A Simple Framework for Self-supervised Collaborative Filtering. arXiv 2021

• UPRec: User-Aware Pre-training for Recommender Systems. arXiv 2021

• Curriculum Pre-Training Heterogeneous Subgraph Transformer for Top-N Recommendation. arXiv 2021

• One4all User Representation for Recommender Systems in E-commerce. arXiv 2021

• Graph Neural Pre-training for Enhancing Recommendations using Side Information. arXiv 2021

• MaHRL: Multi-goals Abstraction based Deep Hierarchical Reinforcement Learning for Recommendations. SIGIR 2020

• Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning. SIGIR 2020

• Joint Policy-Value Learning for Recommendation. KDD 2020

• BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals. KDD 2020

• Learning to Collaborate in Multi-Module Recommendation via Multi-Agent Reinforcement Learning without Communication. RecSys 2020

• Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation. AAAI 2021

• User Response Models to Improve a REINFORCE Recommender System. WSDM 2021

• Cost-Effective and Interpretable Job Skill Recommendation with Deep Reinforcement Learning. WWW 2021

• A Multi-Agent Reinforcement Learning Framework for Intelligent Electric Vehicle Charging Recommendation. WWW 2021

• Reinforcement Recommendation with User Multi-aspect Preference. WWW 2021

• RLNF: Reinforcement Learning based Noise Filtering for Click-Through Rate Prediction. SIGIR 2021

• Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning. SIGIR 2021

• Privileged Features Distillation at Taobao Recommendations. KDD 2020

• DE-RRD: A Knowledge Distillation Framework for Recommender System. CIKM 2020

• Bidirectional Distillation for Top-K Recommender System. WWW 2021

• Neural Input Search for Large Scale Recommendation Models. KDD 2020

• Field-aware Embedding Space Searching in Recommender Systems. WWW 2021

• FedFast Going Beyond Average for Faster Training of Federated Recommender Systems. KDD 2020

• Neural Graph Collaborative Filtering. SIGIR 2019

• A Neural Influence Diffusion Model for Social Recommendation. SIGIR 2019

• Graph Neural Networks for Social Recommendation. WWW 2019

• Knowledge Graph Convolutional Networks for Recommender Systems. WWW 2019

• KGAT: Knowledge Graph Attention Network for Recommendation. KDD 2019

• Session-based recommendation with graph neural networks. AAAI 2019

• Graph contextualized self-attention network for session-based recommendation. IJCAI 2019

• Session-based social recommendation via dynamic graph attention networks. WSDM 2019

• Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction. WWW 2019

• Bundle Recommendation with Graph Convolutional Networks. SIGIR 2020

• Sequential Recommendation with Graph Convolutional Networks. SIGIR 2021

• Structured Graph Convolutional Networks with Stochastic Masks for Recommender Systems. SIGIR 2021

• Adversarial-Enhanced Hybrid Graph Network for User Identity Linkage. SIGIR 2021

• Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method. SIGIR 2021

• A Graph-Convolutional Ranking Approach to Leverage the Relational Aspects of User-Generated Content. SIGIR 2021

• Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph Completion. SIGIR 2021

• Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction. SIGIR 2021

• Neural Graph Matching based Collaborative Filtering. SIGIR 2021

• Modeling Intent Graph for Search Result Diversification. SIGIR 2021

• User-Centric Path Reasoning towards Explainable Recommendation. SIGIR 2021

• Joint Knowledge Pruning and Recurrent Graph Convolution for News Recommendation. SIGIR 2021

• Retrieving Complex Tables with Multi-Granular Graph Representation Learning. SIGIR 2021

• Privileged Graph Distillation for Cold-start Recommendation. SIGIR 2021

• Decoupling Representation Learning and Classification for GNN-based Anomaly Detection. SIGIR 2021

• Meta-Inductive Node Classification across Graphs. SIGIR 2021

• Self-supervised Graph Learning for Recommendation. SIGIR 2021

• TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion. SIGIR 2021

• Graph Meta Network for Multi-Behavior Recommendation with Interaction Heterogeneity and Diversity. SIGIR 2021

• AdsGNN: Behavior-Graph Augmented Relevance Modeling in Sponsored Search. SIGIR 2021

• Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization. SIGIR 2021

• WGCN: Graph Convolutional Networks with Weighted Structural Features. SIGIR 2021

• How Dataset Characteristics Affect the Robustness of Collaborative Recommendation Models. SIGIR 2020

• Agreement and Disagreement between True and False-Positive Metrics in Recommender Systems Evaluation. SIGIR 2020

• Critically Examining the Claimed Value of Convolutions over User-Item Embedding Maps for Recommender Systems. CIKM 2020

• On Estimating Recommendation Evaluation Metrics under Sampling. AAAI 2021

• Beyond Point Estimate Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. WSDM 2021

• Bias-Variance Decomposition for Ranking. WSDM 2021

• Theoretical Understandings of Product Embedding for E-commerce Machine Learning. WSDM 2021

• Learning Personalized Risk Preferences for Recommendation. SIGIR 2020

• Distributed Equivalent Substitution Training for Large-Scale Recommender Systems. SIGIR 2020

• Beyond User Embedding Matrix: Learning to Hash for Modeling Large-Scale Users in Recommendation. SIGIR 2020

• How to Retrain a Recommender System? SIGIR 2020

• Recommendation for New Users and New Items via Randomized Training and Mixture-of-Experts Transformation. SIGIR 2020

• Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems. KDD 2020

• Improving Recommendation Quality in Google Drive. KDD 2020

• A Method to Anonymize Business Metrics to Publishing Implicit Feedback Datasets. RecSys 2020

• Exploiting Performance Estimates for Augmenting Recommendation Ensembles. RecSys 2020

• User Simulation via Supervised Generative Adversarial Network. WWW 2021