Recommender Systems Paperlist that I am interested in
Convolutional Matrix Factorization for Document Context-Aware Recommendation [RecSys 2016] [PDF] [code]
Joint Deep Modeling of Users and Items Using Reviews for Recommendation [WSDM 2017][PDF][code]
Multi-Pointer Co-Attention Networks for Recommendation [KDD 2018][PDF][code]
Gated attentive-autoencoder for content-aware recommendation [WSDM 2019][PDF][code]
Session-based Recommendations with Recurrent Neural Networks [ICLR 2016] [PDF][code]
Neural Attentive Session-based Recommendation [CIKM 2017] [PDF][code]
When Recurrent Neural Networks meet the Neighborhood for Session-Based Recommendation [RecSys 2017][PDF]
STAMP: Short-Term Attention/Memory Priority Model for Session-based Recommendation [KDD 2018] [PDF][code]
RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-based Recommendation [AAAI 2019][PDF][code]
Session-based Recommendation with Graph Neural Networks [AAAI 2019][PDF][code]
Streaming Session-based Recommendation [KDD 2019] [PDF]
Session-based Social Recommendation via Dynamic Graph Attention Networks [WSDM 2019][PDF][code]
Sequence and Time Aware Neighborhood for Session-based Recommendations [SIGIR 2019] [PDF]
Performance Comparison of Neural and Non-Neural Approaches to Session-based Recommendation [RecSys 2019][PDF]
Predictability Limits in Session-based Next Item Recommendation [RecSys 2019][PDF]
Empirical Analysis of Session-Based Recommendation Algorithms [2019] [PDF][code]
A Collaborative Session-based Recommendation Approach with Parallel Memory Modules [SIGIR2019][PDF] [code]
Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks [CIKM2019][PDF]
Session-based Recommendation with Hierarchical Memory Networks [CIKM2019] [PDF]
ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation [IJCAI2019][PDF]
TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation [SIGIR2020][PDF][code]
Star Graph Neural Networks for Session-based Recommendation[CIKM2020][PDF]
Session-based Recommendation with Hierarchical Leaping Networks[SIGIR2020]][PDF]
Handling Information Loss of Graph Neural Networks for Session-based Recommendation[KDD2020][PDF][code]
Incorporating User Micro-behaviors and Item Knowledge into Multi-task Learning for Session-based Recommendation[SIGIR2020][PDF][code]
Session-aware Linear Item-Item Models for Session-based Recommendation [WWW2021] [PDF][code]
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction [[IJCAI 2017] [PDF] [Huawei]
xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems] [KDD2018] [PDF] [Microsoft]
Order-aware Embedding Neural Network for CTR Prediction][SIGIR 2019] [PDF] [Huawei]
Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction [WWW 2019] [PDF] [Huawei]
Interaction-aware Factorization Machines for Recommender Systems [AAAI2019] [PDF][code][Tencent]
[Embedding] Item2Vec-Neural Item Embedding for Collaborative Filtering [Microsoft 2017][PDF]
[Embedding] DeepWalk- Online Learning of Social Representations [KDD 2014][PDF]
[Embedding] LINE - Large-scale Information Network Embedding [Microsoft 2015][PDF]
[Embedding] Node2vec - Scalable Feature Learning for Networks [Stanford 2016][PDF]
[Embedding] Structural Deep Network Embedding [KDD2016] [PDF]
[Embedding] Item2Vec-Neural Item Embedding for Collaborative Filtering [Microsoft 2017][PDF]
[Embedding] Real-time Personalization using Embeddings for Search Ranking at Airbnb [KDD 2018] [PDF]
[Embedding] Graph Convolutional Neural Networks for Web-Scale Recommender Systems [KDD 2018] [PDF][Pinterest]
Is a Single Embedding Enough ? Learning Node Representations that Capture Multiple Social Contexts [WWW 2019] [PDF]
[Embedding] Representation Learning for Attributed Multiplex Heterogeneous Network [KDD 2019] [PDF]
[DNN Match] Deep Neural Networks for YouTube Recommendations [RecSys 2016] [PDF][Youtube]
[DNN Match] Sampling-Bias-Corrected Neural Modeling for Large Corpus Item Recommendations[RecSys 2019] [PDF]
[Semantic Match] Deep Semantic Matching for Amazon Product Search [WSDM 2019][PDF][Amazon]
[Tree Match] Joint Optimization of Tree-based Index and Deep Model for Recommender Systems [NeurIPS 2019] [PDF][Tencent]
Latent Cross: Making Use of Context in Recurrent Recommender Systems [WSDM 2018][PDF][Youtube]
Learning from History and Present: Next-item Recommendation via Discriminatively Exploting Users Behaviors [KDD 2018][PDF]
Real-time Attention Based Look-alike Model for Recommender System [KDD 2019] [PDF] [Tencent]
[Match] TDM:Learning Tree-based Deep Model for Recommender Systems [KDD2018] [PDF]
[Match] Multi-Interest Network with Dynamic Routing for Recommendation at Tmall [2019][PDF]
[Long and short-term] SDM: Sequential Deep Matching Model for Online Large-scale Recommender System [CIKM 2019][PDF]
[Embedding] Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba [KDD 2018][PDF]
[Embedding] Learning and Transferring IDs Representation in E-commerce [KDD 2018] [PDF]
[Representations] ATRank: An Attention-Based User Behavior Modeling Framework for Recommendation [AAAI 2018] [PDF]
[Representations] Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks [KDD2018][PDF]
[exact-K recommendation] Exact-K Recommendation via Maximal Clique Optimization [KDD 2019][PDF]
[Explain]A Capsule Network for Recommendation and Explaining What You Like and Dislike [SIGIR2019][PDF][code]
[CTR] Privileged Features Distillation for E-Commerce Recommendations [Woodstock ’18][PDF]
[CTR] Representation Learning-Assisted Click-Through Rate Prediction [IJCAI 2019] [PDF]
[CTR] Deep Session Interest Network for Click-Through Rate Prediction [IJCAI 2019] [PDF]
[CTR] Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction] [KDD2019] [PDF] [code]
[CTR] Graph Intention Network for Click-through Rate Prediction in Sponsored Search [SIGIR2019] [PDF]
[CTR] Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction [MLR][PDF]
[CTR] Deep Interest Evolution Network for Click-Through Rate Prediction [AAAI2019][PDF]
[CTR] Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction[KDD2019] [PDF][code]
[CTR] Behavior Sequence Transformer for E-commerce Recommendation in Alibaba [PDF]
[CVR] Entire Space Multi-Task Model: An E ective Approach for Estimating Post-Click Conversion Rate [SIGIR2018][PDF]
[CTR] Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction [SIGIR2019] [PDF] [code]
[CTR] Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction[Interpretation]