Recommender System Papers

Overview

Awesome-RSPapers

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

Task

Collaborative Filtering

  • 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

Sequential/Session-based Recommendations

  • 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

Knowledge-aware Recommendations

  • 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

Feature Interactions

  • 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

Conversational Recommender System

  • 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

Social Recommendations

  • 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

News Recommendation

  • 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

Text-aware Recommendations

  • 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

POI

  • 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

Online Recommendations

  • 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

Group Recommendation

  • 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

Multi-task/Multi-behavior/Cross-domain Recommendations

  • 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

Other Task

  • 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

Topic

Debias in Recommender System

  • 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

Fairness in Recommender System

  • 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

Attack in Recommender System

  • 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

Explanation in Recommender System

  • 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

Long-tail/Cold-start in Recommendations

  • 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

Evaluation

  • 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

Technique

Pre-training in Recommender System

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

Reinforcement Learning in Recommendations

  • 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

Knowledge Distillation in Recommendations

  • 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

NAS in Recommendations

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

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

Federated Learning in Recommendations

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

Analysis

  • 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

Other

  • 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

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