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

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

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

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-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

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

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

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

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

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

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

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