/Recommendation-systems-paperlist

Papers about recommendation systems that I am interested in

Recommendation_systems_paperlist

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Survey paper

  • Recommender systems survey [Knowledge-based systems 2013]
  • Deep Learning based Recommender System: A Survey and New Perspectives [2017]
  • A Survey on Session-based Recommender System [2019] [pdf]

Recommendation Systems with Social Information

  • SoRec: Social Recommendation Using Probabilistic Matrix Factorization [CIKM 2008]
  • A Matrix Factorization Technique with Trust Propagation for Recommendation in Social Networks [RecSys 2010]
  • Recommender systems with social regularization [WSDM 2011]
  • On Deep Learning for Trust-Aware Recommendations in Social Networks [IEEE 2017]
  • Learning to Rank with Trust and Distrust in Recommender Systems [RecSys 2017]
  • Social Attentional Memory Network: Modeling Aspect- and Friend-level Differences in Recommendation [WSDM 2019]
  • Session-based Social Recommendation via Dynamic Graph Attention Networks [WSDM 2019]
  • Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems [WWW 2019]
  • Heterogeneous Graph Attention Network [WWW 2019]
  • Graph Neural Networks for Social Recommendation [WWW 2019]
  • GhostLink: Latent Network Inference for Influence-aware Recommendation [WWW 2019]
  • SamWalker: Social Recommendation with Informative Sampling Strategy [WWW 2019]
  • Social Recommendation with Optimal Limited Attention [KDD 2019]
  • Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction [KDD 2019]

Recommendation Systems with Text Information

Topic-based approach

  • Collaborative topic modeling for recommending scientific articles [KDD 2011]
  • Hidden factors and hidden topics: understanding rating dimensions with review text [RecSys 2013]
  • Jointly modeling aspects, ratings and sentiments for movie recommendation [KDD 2014]
  • Ratings meet reviews, a combined approach to recommend [RecSys 2014]
  • Exploring User-Specific Information in Music Retrieval [SIGIR 2018]
  • Aspect-Aware Latent Factor Model: Rating Prediction with Ratings and Reviews [WWW 2018]
  • Exploiting Ratings, Reviews and Relationships for Item Recommendations in Topic Based Social Networks [WWW 2019]

Deep learning-based approach

  • Collaborative deep learning for recommender systems [KDD 2015]
  • Convolutional Matrix Factorization for Document Context-Aware Recommendation [RecSys 2016]
  • Joint Deep Modeling of Users and Items Using Reviews for Recommendation [WSDM 2017]
  • Transnets: Learning to transform for recommendation [RecSys 2017]
  • Latent Cross: Making Use of Context in Recurrent Recommender Systems [WSDM 2018]
  • Coevolutionary Recommendation Model: Mutual Learning between Ratings and Reviews [WWW 2018]
  • Neural Attentional Rating Regression with Review-level Explanations [WWW 2018]
  • Learning Personalized Topical Compositions with Item Response Theory [WSDM 2019]
  • Uncovering Hidden Structure in Sequence Data via Threading Recurrent Models [WSDM 2019]
  • Gated Attentive-Autoencoder for Content-Aware Recommendation [WSDM 2019]
  • DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation [KDD 2019]
  • Attentive Aspect Modeling for Review-Aware Recommendation [TOIS 2019]
  • Reviews Meet Graphs: Enhancing User and Item Representations for Recommendation with Hierarchical Attentive Graph Neural Network [EMNLP 2019]

Explainable Recommendation Systems

  • Social Collaborative Viewpoint Regression with Explainable Recommendations [WSDM 2017]
  • Explainable Recommendation via Multi-Task Learning in Opinionated Text Data [SIGIR 2018]
  • TEM: Tree-enhanced Embedding Model for Explainable Recommendation [WWW 2018]
  • Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspects [EMNLP 2019]
  • Dynamic Explainable Recommendation based on Neural Attentive Models [AAAI 2019]

Session-Based Recommendation Systems

Markov-chain based approach

  • Factorizing Personalized Markov Chains for Next-Basket Recommendation [WWW 2010]
  • Where You Like to Go Next: Successive Point-of-Interest Recommendation [IJCAI 2013]
  • Learning Hierarchical Representation Model for NextBasket Recommendation [SIGIR 2015]
  • Fusing Similarity Models with Markov Chains for Sparse Sequential Recommendation [ICDM 2016]
  • Translation-based Recommendation [RecSys 2017]

RNN based approach

  • Session-based Recommendations with Recurrent Neural Networks [ICLR 2016]
  • Neural Attentive Session-based Recommendation [CIKM 2017]
  • Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks [RecSys 2017]
  • When Recurrent Neural Networks meet the Neighborhood for Session-Based Recommendation [RecSys 2017]
  • Modeling User Session and Intent with an Attention-based Encoder-Decoder Architecture [RecSys 2017]
  • Learning from History and Present: Next-item Recommendation via Discriminatively Exploting Users Behaviors [KDD 2018]
  • Recurrent Neural Networks with Top-k Gains for Session-based Recommendations [CIKM 2018]
  • Hierarchical Context enabled Recurrent Neural Network for Recommendation. [AAAI 2019]
  • RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-based Recommendation [AAAI 2019]
  • Time is of the Essence: a Joint Hierarchical RNN and Point Process Model for Time and Item Predictions [WSDM 2019]
  • Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks [KDD 2019]
  • AIR: Attentional Intention-Aware Recommender Systems [ICDE 2019]

CNN based approach

Graph based approach

Other approach

  • Diversifying Personalized Recommendation with User-session Context [IJCAI 2017]
  • Translation-based Factorization Machines for Sequential Recommendation [RecSys 2018]
  • Attention-Based Transactional Context Embedding for Next-Item Recommendation [AAAI 2018]
  • STAMP: Short-Term Attention/Memory Priority Model for Session-based Recommendation [KDD 2018]
  • Self-Attentive Sequential Recommendation [ICDM 2018]
  • Taxonomy-aware Multi-hop Reasoning Networks for Sequential Recommendation [WSDM 2019]
  • Hierarchical Neural Variational Model for Personalized Sequential Recommendation [WWW 2019]
  • BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer [CIKM 2019]
  • Hierarchical Gating Networks for Sequential Recommendation [KDD 2019]
  • Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics [KDD 2019]
  • Streaming Session-based Recommendation [KDD 2019]
  • Log2Intent: Towards Interpretable User Modeling via Recurrent Semantics Memory Unit [KDD 2019]

News Recommendation

  • Google news personalization: scalable online collaborative filtering [WWW 2007]
  • Personalized News Recommendation Based on Click Behavior [IUI 2009]
  • Personalized News Recommendation Using Twitter [IEEE 2013]
  • Recommending Personalized News in Short User Sessions [RecSys 2017]
  • Embedding-based News Recommendation for Millions of Users [KDD 2017]
  • DKN: Deep Knowledge-Aware Network for News Recommendation [WWW 2018]
  • NPA: Neural News Recommendation with Personalized Attention [KDD 2019]
  • Neural News Recommendation with Heterogeneous User Behavior [EMNLP 2019]
  • Neural News Recommendation with Multi-Head Self-Attention [EMNLP 2019]

Video Recommendation

  • Video suggestion and discovery for youtube: taking random walks through the view graph [WWW 2008]
  • The YouTube Video Recommendation System [RecSys 2010]
  • Deep Neural Networks for YouTube Recommendations [RecSys 2016]
  • Wide & Deep Learning for Recommender Systems [DLRS 2016]
  • Content-based Related Video Recommendations [NIPS 2016]

Music Recommendation

  • Playlist prediction via metric embedding [KDD 2012]
  • Deep content-based music recommendation [NIPS 2013]
  • Improving Content-based and Hybrid Music Recommendation using Deep Learning [MM 2014]
  • Content-aware collaborative music recommendation using pre-trained neural networks [ISMIR 2015]

Automatic Playlist Continuation

Route Recommendation

  • Effective and Efficient Reuse of Past Travel Behavior for Route Recommendation [KDD 2019]
  • Empowering A* Search Algorithms with Neural Networks for Personalized Route Recommendation [KDD 2019]

Image Recommendation

  • Pagerank for product image search [WWW 2008]
  • Related Pins at Pinterest: The Evolution of a Real-World Recommender System [WWW 2017]
  • Pixie: A System for Recommending 3+ Billion Items to 200+ Million Users in Real-Time [WWW 2018]

Time-aware Recommendation (Temporal Dynamics)

  • Time Weight Collaborative Filtering [CIKM 2005]
  • Collaborative Filtering with Temporal Dynamics [KDD 2009]
  • Opportunity Models for E-commerce Recommendation: Right Product, Right Time [SIGIR 2013]
  • Multi-rate deep learning for temporal recommendation [SIGIR 2016]
  • Recurrent Recommender Networks [WSDM 2017]
  • Recurrent Recommendation with Local Coherence [WSDM 2019]

Reinforcement Learning

  • Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning [NeurlPS 2019]
  • Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation [NeurlPS 2019]

Multi-Armed Bandit

  • A Contextual-Bandit Approach to Personalized News Article Recommendation [WWW 2010]
  • A survey of online experiment design with the stochastic multi-armed bandit [2015] [pdf]
  • Collaborative filtering as a multi-armed bandit [NIPS 2015]
  • Online Context-Aware Recommendation with Time Varying Multi-Arm Bandit [KDD 2016]
  • Collaborative Filtering Bandits [SIGIR 2016]

Cold-start Problem

  • MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation [KDD 2019]

Out of Category

  • Learning Multiple Similarities of Users and Items in Recommender Systems [ICDM 2017]
  • Neural Collaborative Filtering [WWW 2017]
  • MRNet-Product2Vec: A Multi-task Recurrent Neural Network for Product Embeddings [ECML-PKDD 2017]
  • A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation [RecSys 2017]
  • IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models [SIGIR 2017]
  • Collaborative Memory Network for Recommendation Systems [SIGIR 2018]
  • Variational Autoencoders for Collaborative Filtering [WWW 2018]
  • Latent Relational Metric Learning via Memory-based Attention for Collaborative Ranking [WWW 2018]
  • Causal Embeddings for Recommendation [RecSys 2018]
  • Linked Variational AutoEncoders for Inferring Substitutable and Supplementary Items [WSDM 2019]
  • RecWalk: Nearly Uncoupled Random Walks for Top-N Recommendation [WSDM 2019]