kiminh / recsys-papers-from-sigir-2020

Full papers related to the Recommender System from SIGIR 2020

RecSys-Papers-from-SIGIR-2020

Full papers related to the Recommender System from SIGIR 2020

Interesting Papers (5 papers)

• How Dataset Characteristics Affect the Robustness of Collaborative Recommendation Models
• Try This Instead: Personalized and Interpretable Substitute Recommendation
• How to Retrain a Recommender System?
• Web-to-Voice Transfer for Product Recommendation on Voice
• The Impact of More Transparent Interfaces on Behavior in Personalized Recommendation

Explainable Recommendations (3 papers)

• Fairness-Aware Explainable Recommendation over Knowledge Graphs
• Measuring Recommendation Explanation Quality: The Conflicting Goals of Explanations
• Try This Instead: Personalized and Interpretable Substitute Recommendation

Cross-Domain Recommendations (2 papers)

• CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network
• Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation

Interactive Recommendations (4 papers)

• Neural Interactive Collaborative Filtering
• Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning
• Towards Question-based Recommender Systems
• Deep Critiquing for VAE-based Recommender Systems

Group Recommendation (3 papers)

• Group-Aware Long- and Short-Term Graph Representation Learning for Sequential Group Recommendation
• GroupIM: A Mutual Information Maximizing Framework for Neural Group Recommendation
• GAME: Learning Graphical and Attentive Multi-view Embeddings for Occasional Group Recommendation

Session-based & Sequential Recommendations (10 papers)

• Global Context Enhanced Graph Neural Networks for Session-based Recommendation
• GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation
• Incorporating User Micro-behaviors and Item Knowledge into Multi-task Learning for Session-based Recommendation
• Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation
• Time Matters: Sequential Recommendation with Complex Temporal Information
• Group-Aware Long- and Short-Term Graph Representation Learning for Sequential Group Recommendation
• KERL: A Knowledge-Guided Reinforcement Learning Model for Sequential Recommendation
• Next-item Recommendation with Sequential Hypergraphs
• A General Network Compression Framework for Sequential Recommender Systems
• Sequential Recommendation with Self-attentive Multi-adversarial Network

Graph-based Recommendations (18 papers)

• Disentangled Representations for Graph-based Collaborative Filtering
• Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning
• Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs
• GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Identification
• Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach
• Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation
• Global Context Enhanced Graph Neural Networks for Session-based Recommendation
• Group-Aware Long- and Short-Term Graph Representation Learning for Sequential Group Recommendation
• Next-item Recommendation with Sequential Hypergraphs
• Neighbor Interaction Aware Graph Convolution Networks for Recommendation
• GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation
• Hierarchical Fashion Graph Network for Personalized Outfit Recommendation
• Multi-behavior Recommendation with Graph Convolution Networks
• GAME: Learning Graphical and Attentive Multi-view Embeddings for Occasional Group Recommendation
• Lightening Graph Convolution Network for Recommendation
• Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View
• Fairness-Aware Explainable Recommendation over Knowledge Graphs
• Jointly Non-Sampling Learning for Knowledge Graph Enhanced Recommendation

Reinforcement Learning (5 papers)

• Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning
• Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs
• MaHRL: Multi-goals Abstraction based Deep Hierarchical Reinforcement Learning for Recommendations
• Self-Supervised Reinforcement Learning for Recommender Systems
• KERL: A Knowledge-Guided Reinforcement Learning Model for Sequential Recommendation

Cold-Start Problems (5 papers)

• AR-CF: Augmenting Virtual Users and Items in Collaborative Filtering for Addressing Cold-Start Problems
• CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network
• Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste
• Content-aware Neural Hashing for Cold-start Recommendation
• Recommendation for New Users and New Items via Randomized Training and Mixture-of-Experts Transformation

Scalability & Efficiency (4 papers)

• Beyond User Embedding Matrix: Learning to Hash for Modeling Large-Scale Users in Recommendation
• Distributed Equivalent Substitution Training for Large-Scale Recommender Systems
• Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation
• A General Network Compression Framework for Sequential Recommender Systems

Evaluation (3 papers)

• Agreement and Disagreement between True and False-Positive Metrics in Recommender Systems Evaluation
• Measuring and Mitigating Item Under-Recommendation Bias in Personalized Ranking Systems
• Measuring Recommendation Explanation Quality: The Conflicting Goals of Explanations

Applications (4papers)

• Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste
• Hierarchical Fashion Graph Network for Personalized Outfit Recommendation
• Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View
• HME: A Hyperbolic Metric Embedding Approach for Next-POI Recommendation