추천시스템 관련 논문

ㅇ  Survey paper

   - Deep Learning based Recommender System: A Survey and New Perspectives

     (Zhang et al. 2019

 

ㅇ Matrix Factorization 

   - BPR: Bayesian Personalized Ranking from Implict Feedback

     (Steffen Rendle, UAI 2009)

 

ㅇ Context-Aware-recommend system

   - STELLAR : Spatial-Temporal Latent Ranking for Successive Point-of-Interest Recommendation

     (Shenglin Zhao, et al. Published in AAAI 2016)

   - LARS: A Location-Aware Recommender System

     (Justin J.Levandoski, 2012 IEEE)

 

ㅇ Deep learning-recommend system

    - Neural collaborative Filtering 

      (2017 indernational world wide web conference)

 

    - Factorization Machines (DeepFM을 알기 위한 논문. 딥러닝 관련은 X. 머신러닝의 svm과 비슷)

      (2010 IEEE international conference on Data Mining)

 

    - Wide and Deep Learning for Recommender System (추천시스템 서비스 제공 측면에서도 잘 설명)

      (Google)                                                         (피처를 전처리할때 좋음)

 

 

    - DeepFM : A Factorization-Machine based Neural Network for CTR Prediction (일반적인 모델에 좋음)

      (26th International Joint Conference on Artificial Intelligence 2017)

 

    - AutoRec : Autoencoders Meet Collaborative Filtering (Autoencoder)

      (2015 WWW Conference)  

 

    - Training Deep AutoEncoders for Collaborative Filtering (Autoencoder)

      (2017, NVIDIA)

 

    - Variational Autoencoders for Collaborative Filtering (Autoencoder)

      (2018, Google, netflix, Mit)

 

ㅇ Sequential한 Data

    - Session-based Recommendations with Recurrent Neural Networks

      (2016, ICLR)

       

    - BERT4Rec:Sequential Recommendation with Bidirectional Encoder Representations from Transformer

      (2019 Sun et al.)       

 

ㅇ Text 활용

    - Recurrent recommender Networks

      (WSDM '17: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining 2017)

 

    - Joint Training of Ratings and reviews with Recurrent recommender Networks

      (Workshop on ICLR 2017)

 

ㅇ Image 활용

    - Image_based Recommendations on Styles and Substitutes

     (Julian McAuley, SIGIR 2015)

 

   - VBPR:Visual Bayesian Personalized Ranking from Implict Feedback

     (He et al , 2015)

 

ㅇ Music

   - Deep content-based music recommendation

     (2013 NIPS)

 

ㅇ YouTube Recommender System

   - The YouTube Video Recommendation System

     (Nandy et al., 2010 RecSys)

 

   - Deep Neural Networks for YouTube Recommendations

     (Covington et al., 2016 RecSys)

 

   - Recommending what video to watch next: a multitask ranking system

     (Zhao et al., (2019 RecSys)