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Recommender Systems

1,030 papers

Papers per year

9
15
98
156
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Papers

Improving Sequential Recommendation Consistency with Self-Supervised Imitation IJCAI 2021
User Retention: A Causal Approach with Triple Task Modeling IJCAI 2021
Recent Advances in Heterogeneous Relation Learning for Recommendation IJCAI 2021
Graph Learning based Recommender Systems: A Review IJCAI 2021
Deep Learning for Click-Through Rate Estimation IJCAI 2021
Cross-Domain Recommendation: Challenges, Progress, and Prospects IJCAI 2021
On Sampled Metrics for Item Recommendation (Extended Abstract) IJCAI 2021
Unsupervised Extractive Summarization-Based Representations for Accurate and Explainable Collaborative Filtering IJCNLP 2021
HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation IJCNLP 2021
PP-Rec: News Recommendation with Personalized User Interest and Time-aware News Popularity IJCNLP 2021
Keyword Augmentation via Generative Methods IJCNLP 2021
Sparse Tensor Additive Regression JMLR 2021
Dynamic Tensor Recommender Systems JMLR 2021
OpenML-Python: an extensible Python API for OpenML JMLR 2021
Trading Personalization for Accuracy: Data Debugging in Collaborative Filtering NIPS 2020
Simultaneous Preference and Metric Learning from Paired Comparisons NIPS 2020
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering NIPS 2020
CodeCMR: Cross-Modal Retrieval For Function-Level Binary Source Code Matching NIPS 2020
Matrix Completion with Hierarchical Graph Side Information NIPS 2020
Adversarial Counterfactual Learning and Evaluation for Recommender System NIPS 2020
Online Matrix Completion with Side Information NIPS 2020
Regret in Online Recommendation Systems NIPS 2020
Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation AAAI 2020
Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach AAAI 2020
Question-Driven Purchasing Propensity Analysis for Recommendation AAAI 2020