{ "id": 376977, "title": "Journal Papers about Recommender Systems", "url": "/competitions/otto-recommender-system/discussion/376977", "author_name": "", "post_date": "2023-01-09T11:52:19.896803Z", "votes": 12, "comment_count": 1, "views": 0, "content": "

This is a list with journal papers (ordered chronologically) about Recommender Systems

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
PaperAuthorsLinkYear
GroupLens: An Open Architecture for Collaborative Filtering of NetnewsPaul Resnick, Neophytos Iacovou, Mitesh Suchak, Peter Bergstrom, John Riedlhttp://ccs.mit.edu/papers/CCSWP165.html1994
Application of Dimensionality Reduction in Recommender System -- A Case StudyBadrul M. Sarwar, George Karypis, Joseph A. Konstan, Juhn T. RiedlDim Red in Rec Sys, 20002000
Collaborative Filtering for Implicit Feedback DatasetsYifan Hu, Yehuda Koren, Chris Volinskyhttp://yifanhu.net/PUB/cf.pdf2008
Matrix Factorization Techniques for Recommender SystemsYehuda Koren, Robert Bell, Chris VolinskyRecSys Netflix 20092009
Feature-Based Matrix FactorizationTianqi Chen, Zhao Zheng, Qiuxia Lu, Weinan Zhang, Yong Yuhttps://arxiv.org/pdf/1109.2271.pdf2011
SLIM: Sparse Linear Methods for Top-N Recommender SystemsXia Ning and George KarypisSLIM Paper 20112011
Factorization Machines with libFMSteffen RendleFactorization Machines with libFM, 20122012
Local Low-Rank Matrix ApproximationJoonseok Lee,  Seungyeon Kim, Guy Lebanon, Yoram SingerGoogle Research 20142013
Logistic Matrix Factorization for Implicit Feedback DataChristopher C. JohnsonSpotify 20142014
Session-based Recommendations with Recurrent Neural NetworksBalázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, Domonkos Tikkhttps://arxiv.org/pdf/1511.06939.pdf2015
E-commerce in Your Inbox: Product Recommendations at ScaleMihajlo Grbovic, Vladan Radosavljevic, Nemanja Djuric, Narayan Bhamidipati, Jaikit Savla, Varun Bhagwan, Doug Sharphttps://arxiv.org/pdf/1606.07154.pdf2016
Deep Neural Networks for YouTube RecommendationsPaul Covington, Jay Adams, Emre SarginDeep Neural Networks for YouTube Recommendations2016
Item2Vec: Neural Item Embedding for Collaborative FilteringOren Barkan, Noam Koenigsteinhttps://arxiv.org/ftp/arxiv/papers/1603/1603.04259.pdf2017
Fast Matrix Factorization for Online Recommendation with Implicit FeedbackXiangnan He, Hanwang Zhang, Min-Yen Kan, Tat-Seng Chuahttps://arxiv.org/pdf/1708.05024.pdf2017
Translation-based RecommendationRuining He, Wang-Cheng Kang, Julian McAuleyhttps://arxiv.org/pdf/1707.02410.pdf2017
Metric Factorization: Recommendation beyond Matrix FactorizationShuai Zhang, Lina Yao, Yi Tay, Xiwei Xu, Xiang Zhang, Liming Zhuhttps://arxiv.org/pdf/1802.04606.pdf2018
Spectral Collaborative FilteringLei Zheng, Chun-Ta Lu, Fei Jiang, Jiawei Zhang, Philip S. Yuhttps://arxiv.org/pdf/1808.10523.pdf2018
RecGAN: recurrent generative adversarial networks for recommendation systemsHomanga Bharadhwaj, Homin ParkBrian, LimBrian LimRecGAN paper 20182018
Neural Graph Collaborative FilteringXiang Wang, Xiangnan He, Meng Wang, Fuli Feng, Tat-Seng Chuahttps://arxiv.org/pdf/1905.08108.pdf2019
Neural Collaborative Filtering vs. Matrix Factorization RevisitedSteffen Rendle, Walid Krichene, Li Zhang, John Andersonhttps://arxiv.org/pdf/2005.09683.pdf2021
Monolith: Real Time Recommendation System With Collisionless Embedding TableZhuoran Liu, Leqi Zou, Xuan Zou, Caihua Wang, Biao Zhang, Da Tang, Bolin Zhu, Yijie Zhu, Peng Wu, Ke Wang, Youlong Chenghttps://arxiv.org/pdf/2209.07663.pdf2022
", "messages": [ { "id": "2092514", "postDate": "01/09/2023 11:52:19", "content": "

This is a list with journal papers (ordered chronologically) about Recommender Systems

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
PaperAuthorsLinkYear
GroupLens: An Open Architecture for Collaborative Filtering of NetnewsPaul Resnick, Neophytos Iacovou, Mitesh Suchak, Peter Bergstrom, John Riedlhttp://ccs.mit.edu/papers/CCSWP165.html1994
Application of Dimensionality Reduction in Recommender System -- A Case StudyBadrul M. Sarwar, George Karypis, Joseph A. Konstan, Juhn T. RiedlDim Red in Rec Sys, 20002000
Collaborative Filtering for Implicit Feedback DatasetsYifan Hu, Yehuda Koren, Chris Volinskyhttp://yifanhu.net/PUB/cf.pdf2008
Matrix Factorization Techniques for Recommender SystemsYehuda Koren, Robert Bell, Chris VolinskyRecSys Netflix 20092009
Feature-Based Matrix FactorizationTianqi Chen, Zhao Zheng, Qiuxia Lu, Weinan Zhang, Yong Yuhttps://arxiv.org/pdf/1109.2271.pdf2011
SLIM: Sparse Linear Methods for Top-N Recommender SystemsXia Ning and George KarypisSLIM Paper 20112011
Factorization Machines with libFMSteffen RendleFactorization Machines with libFM, 20122012
Local Low-Rank Matrix ApproximationJoonseok Lee,  Seungyeon Kim, Guy Lebanon, Yoram SingerGoogle Research 20142013
Logistic Matrix Factorization for Implicit Feedback DataChristopher C. JohnsonSpotify 20142014
Session-based Recommendations with Recurrent Neural NetworksBalázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, Domonkos Tikkhttps://arxiv.org/pdf/1511.06939.pdf2015
E-commerce in Your Inbox: Product Recommendations at ScaleMihajlo Grbovic, Vladan Radosavljevic, Nemanja Djuric, Narayan Bhamidipati, Jaikit Savla, Varun Bhagwan, Doug Sharphttps://arxiv.org/pdf/1606.07154.pdf2016
Deep Neural Networks for YouTube RecommendationsPaul Covington, Jay Adams, Emre SarginDeep Neural Networks for YouTube Recommendations2016
Item2Vec: Neural Item Embedding for Collaborative FilteringOren Barkan, Noam Koenigsteinhttps://arxiv.org/ftp/arxiv/papers/1603/1603.04259.pdf2017
Fast Matrix Factorization for Online Recommendation with Implicit FeedbackXiangnan He, Hanwang Zhang, Min-Yen Kan, Tat-Seng Chuahttps://arxiv.org/pdf/1708.05024.pdf2017
Translation-based RecommendationRuining He, Wang-Cheng Kang, Julian McAuleyhttps://arxiv.org/pdf/1707.02410.pdf2017
Metric Factorization: Recommendation beyond Matrix FactorizationShuai Zhang, Lina Yao, Yi Tay, Xiwei Xu, Xiang Zhang, Liming Zhuhttps://arxiv.org/pdf/1802.04606.pdf2018
Spectral Collaborative FilteringLei Zheng, Chun-Ta Lu, Fei Jiang, Jiawei Zhang, Philip S. Yuhttps://arxiv.org/pdf/1808.10523.pdf2018
RecGAN: recurrent generative adversarial networks for recommendation systemsHomanga Bharadhwaj, Homin ParkBrian, LimBrian LimRecGAN paper 20182018
Neural Graph Collaborative FilteringXiang Wang, Xiangnan He, Meng Wang, Fuli Feng, Tat-Seng Chuahttps://arxiv.org/pdf/1905.08108.pdf2019
Neural Collaborative Filtering vs. Matrix Factorization RevisitedSteffen Rendle, Walid Krichene, Li Zhang, John Andersonhttps://arxiv.org/pdf/2005.09683.pdf2021
Monolith: Real Time Recommendation System With Collisionless Embedding TableZhuoran Liu, Leqi Zou, Xuan Zou, Caihua Wang, Biao Zhang, Da Tang, Bolin Zhu, Yijie Zhu, Peng Wu, Ke Wang, Youlong Chenghttps://arxiv.org/pdf/2209.07663.pdf2022
", "rawMarkdown": "This is a list with journal papers (ordered chronologically) about Recommender Systems\n\n\n| Paper | Authors | Link | Year |\n| ----------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------- | ---- |\n| GroupLens: An Open Architecture for Collaborative Filtering of Netnews | Paul Resnick, Neophytos Iacovou, Mitesh Suchak, Peter Bergstrom, John Riedl | [http://ccs.mit.edu/papers/CCSWP165.html](http://ccs.mit.edu/papers/CCSWP165.html) | 1994 |\n| Application of Dimensionality Reduction in Recommender System -- A Case Study | Badrul M. Sarwar, George Karypis, Joseph A. Konstan, Juhn T. Riedl | [Dim Red in Rec Sys, 2000](https://www.researchgate.net/publication/2824548_Application_of_DimenRi) | 2000 |\n| Collaborative Filtering for Implicit Feedback Datasets | Yifan Hu, Yehuda Koren, Chris Volinsky | [http://yifanhu.net/PUB/cf.pdf](http://yifanhu.net/PUB/cf.pdf) | 2008 |\n| Matrix Factorization Techniques for Recommender Systems | Yehuda Koren, Robert Bell, Chris Volinsky | [RecSys Netflix 2009](https://datajobs.com/data-science-repo/Recommender-Systems-%5bNetflix%5d.pdf) | 2009 |\n| Feature-Based Matrix Factorization | Tianqi Chen, Zhao Zheng, Qiuxia Lu, Weinan Zhang, Yong Yu | [https://arxiv.org/pdf/1109.2271.pdf](https://arxiv.org/pdf/1109.2271.pdf) | 2011 |\n| SLIM: Sparse Linear Methods for Top-N Recommender Systems | Xia Ning and George Karypis | [SLIM Paper 2011](http://glaros.dtc.umn.edu/gkhome/fetch/papers/SLIM2011icdm.pdf) | 2011 |\n| Factorization Machines with libFM | Steffen Rendle | [Factorization Machines with libFM, 2012](https://www.csie.ntu.edu.tw/~b97053/paper/Factorization%20Machines%20with%20libFM.pdf) | 2012 |\n| Local Low-Rank Matrix Approximation | Joonseok Lee,  Seungyeon Kim, Guy Lebanon, Yoram Singer | [Google Research 2014](https://static.googleusercontent.com/media/research.google.com/en/pubs/archive/45235.pdf) | 2013 |\n| Logistic Matrix Factorization for Implicit Feedback Data | Christopher C. Johnson | [Spotify 2014](https://web.stanford.edu/~rezab/nips2014workshop/submits/logmat.pdf) | 2014 |\n| Session-based Recommendations with Recurrent Neural Networks | Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, Domonkos Tikk | [https://arxiv.org/pdf/1511.06939.pdf](https://arxiv.org/pdf/1511.06939.pdf) | 2015 |\n| E-commerce in Your Inbox: Product Recommendations at Scale | Mihajlo Grbovic, Vladan Radosavljevic, Nemanja Djuric, Narayan Bhamidipati, Jaikit Savla, Varun Bhagwan, Doug Sharp | [https://arxiv.org/pdf/1606.07154.pdf](https://arxiv.org/pdf/1606.07154.pdf) | 2016 |\n| Deep Neural Networks for YouTube Recommendations | Paul Covington, Jay Adams, Emre Sargin | [Deep Neural Networks for YouTube Recommendations](https://static.googleusercontent.com/media/research.google.com/en/pubs/archive/45530.pdf) | 2016 |\n| Item2Vec: Neural Item Embedding for Collaborative Filtering | Oren Barkan, Noam Koenigstein | [https://arxiv.org/ftp/arxiv/papers/1603/1603.04259.pdf](https://arxiv.org/ftp/arxiv/papers/1603/1603.04259.pdf) | 2017 |\n| Fast Matrix Factorization for Online Recommendation with Implicit Feedback | Xiangnan He, Hanwang Zhang, Min-Yen Kan, Tat-Seng Chua | [https://arxiv.org/pdf/1708.05024.pdf](https://arxiv.org/pdf/1708.05024.pdf) | 2017 |\n| Translation-based Recommendation | Ruining He, Wang-Cheng Kang, Julian McAuley | [https://arxiv.org/pdf/1707.02410.pdf](https://arxiv.org/pdf/1707.02410.pdf) | 2017 |\n| Metric Factorization: Recommendation beyond Matrix Factorization | Shuai Zhang, Lina Yao, Yi Tay, Xiwei Xu, Xiang Zhang, Liming Zhu | [https://arxiv.org/pdf/1802.04606.pdf](https://arxiv.org/pdf/1802.04606.pdf) | 2018 |\n| Spectral Collaborative Filtering | Lei Zheng, Chun-Ta Lu, Fei Jiang, Jiawei Zhang, Philip S. Yu | [https://arxiv.org/pdf/1808.10523.pdf](https://arxiv.org/pdf/1808.10523.pdf) | 2018 |\n| RecGAN: recurrent generative adversarial networks for recommendation systems | Homanga Bharadhwaj, Homin ParkBrian, LimBrian Lim | [RecGAN paper 2018](https://www.researchgate.net/publication/327945924_RecGAN_recurrent_generative_adversarial_networks_for_recommendation_systems) | 2018 |\n| Neural Graph Collaborative Filtering | Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, Tat-Seng Chua | [https://arxiv.org/pdf/1905.08108.pdf](https://arxiv.org/pdf/1905.08108.pdf) | 2019 |\n| Neural Collaborative Filtering vs. Matrix Factorization Revisited | Steffen Rendle, Walid Krichene, Li Zhang, John Anderson | [https://arxiv.org/pdf/2005.09683.pdf](https://arxiv.org/pdf/2005.09683.pdf) | 2021 |\n| Monolith: Real Time Recommendation System With Collisionless Embedding Table | Zhuoran Liu, Leqi Zou, Xuan Zou, Caihua Wang, Biao Zhang, Da Tang, Bolin Zhu, Yijie Zhu, Peng Wu, Ke Wang, Youlong Cheng | [https://arxiv.org/pdf/2209.07663.pdf](https://arxiv.org/pdf/2209.07663.pdf) | 2022 |", "votes": null }, { "id": "2092550", "postDate": "01/09/2023 12:20:47", "content": "

thanks for this short summary!

", "rawMarkdown": "thanks for this short summary!", "votes": null } ], "comments": [ { "id": 2092550, "author_name": "mikhailma", "author_url": "", "post_date": "01/09/2023 12:20:47", "content": "

thanks for this short summary!

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "2092514": "This is a list with journal papers (ordered chronologically) about Recommender Systems\n\n\n| Paper | Authors | Link | Year |\n| ----------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------- | ---- |\n| GroupLens: An Open Architecture for Collaborative Filtering of Netnews | Paul Resnick, Neophytos Iacovou, Mitesh Suchak, Peter Bergstrom, John Riedl | [http://ccs.mit.edu/papers/CCSWP165.html](http://ccs.mit.edu/papers/CCSWP165.html) | 1994 |\n| Application of Dimensionality Reduction in Recommender System -- A Case Study | Badrul M. Sarwar, George Karypis, Joseph A. Konstan, Juhn T. Riedl | [Dim Red in Rec Sys, 2000](https://www.researchgate.net/publication/2824548_Application_of_DimenRi) | 2000 |\n| Collaborative Filtering for Implicit Feedback Datasets | Yifan Hu, Yehuda Koren, Chris Volinsky | [http://yifanhu.net/PUB/cf.pdf](http://yifanhu.net/PUB/cf.pdf) | 2008 |\n| Matrix Factorization Techniques for Recommender Systems | Yehuda Koren, Robert Bell, Chris Volinsky | [RecSys Netflix 2009](https://datajobs.com/data-science-repo/Recommender-Systems-%5bNetflix%5d.pdf) | 2009 |\n| Feature-Based Matrix Factorization | Tianqi Chen, Zhao Zheng, Qiuxia Lu, Weinan Zhang, Yong Yu | [https://arxiv.org/pdf/1109.2271.pdf](https://arxiv.org/pdf/1109.2271.pdf) | 2011 |\n| SLIM: Sparse Linear Methods for Top-N Recommender Systems | Xia Ning and George Karypis | [SLIM Paper 2011](http://glaros.dtc.umn.edu/gkhome/fetch/papers/SLIM2011icdm.pdf) | 2011 |\n| Factorization Machines with libFM | Steffen Rendle | [Factorization Machines with libFM, 2012](https://www.csie.ntu.edu.tw/~b97053/paper/Factorization%20Machines%20with%20libFM.pdf) | 2012 |\n| Local Low-Rank Matrix Approximation | Joonseok Lee,  Seungyeon Kim, Guy Lebanon, Yoram Singer | [Google Research 2014](https://static.googleusercontent.com/media/research.google.com/en/pubs/archive/45235.pdf) | 2013 |\n| Logistic Matrix Factorization for Implicit Feedback Data | Christopher C. Johnson | [Spotify 2014](https://web.stanford.edu/~rezab/nips2014workshop/submits/logmat.pdf) | 2014 |\n| Session-based Recommendations with Recurrent Neural Networks | Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, Domonkos Tikk | [https://arxiv.org/pdf/1511.06939.pdf](https://arxiv.org/pdf/1511.06939.pdf) | 2015 |\n| E-commerce in Your Inbox: Product Recommendations at Scale | Mihajlo Grbovic, Vladan Radosavljevic, Nemanja Djuric, Narayan Bhamidipati, Jaikit Savla, Varun Bhagwan, Doug Sharp | [https://arxiv.org/pdf/1606.07154.pdf](https://arxiv.org/pdf/1606.07154.pdf) | 2016 |\n| Deep Neural Networks for YouTube Recommendations | Paul Covington, Jay Adams, Emre Sargin | [Deep Neural Networks for YouTube Recommendations](https://static.googleusercontent.com/media/research.google.com/en/pubs/archive/45530.pdf) | 2016 |\n| Item2Vec: Neural Item Embedding for Collaborative Filtering | Oren Barkan, Noam Koenigstein | [https://arxiv.org/ftp/arxiv/papers/1603/1603.04259.pdf](https://arxiv.org/ftp/arxiv/papers/1603/1603.04259.pdf) | 2017 |\n| Fast Matrix Factorization for Online Recommendation with Implicit Feedback | Xiangnan He, Hanwang Zhang, Min-Yen Kan, Tat-Seng Chua | [https://arxiv.org/pdf/1708.05024.pdf](https://arxiv.org/pdf/1708.05024.pdf) | 2017 |\n| Translation-based Recommendation | Ruining He, Wang-Cheng Kang, Julian McAuley | [https://arxiv.org/pdf/1707.02410.pdf](https://arxiv.org/pdf/1707.02410.pdf) | 2017 |\n| Metric Factorization: Recommendation beyond Matrix Factorization | Shuai Zhang, Lina Yao, Yi Tay, Xiwei Xu, Xiang Zhang, Liming Zhu | [https://arxiv.org/pdf/1802.04606.pdf](https://arxiv.org/pdf/1802.04606.pdf) | 2018 |\n| Spectral Collaborative Filtering | Lei Zheng, Chun-Ta Lu, Fei Jiang, Jiawei Zhang, Philip S. Yu | [https://arxiv.org/pdf/1808.10523.pdf](https://arxiv.org/pdf/1808.10523.pdf) | 2018 |\n| RecGAN: recurrent generative adversarial networks for recommendation systems | Homanga Bharadhwaj, Homin ParkBrian, LimBrian Lim | [RecGAN paper 2018](https://www.researchgate.net/publication/327945924_RecGAN_recurrent_generative_adversarial_networks_for_recommendation_systems) | 2018 |\n| Neural Graph Collaborative Filtering | Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, Tat-Seng Chua | [https://arxiv.org/pdf/1905.08108.pdf](https://arxiv.org/pdf/1905.08108.pdf) | 2019 |\n| Neural Collaborative Filtering vs. Matrix Factorization Revisited | Steffen Rendle, Walid Krichene, Li Zhang, John Anderson | [https://arxiv.org/pdf/2005.09683.pdf](https://arxiv.org/pdf/2005.09683.pdf) | 2021 |\n| Monolith: Real Time Recommendation System With Collisionless Embedding Table | Zhuoran Liu, Leqi Zou, Xuan Zou, Caihua Wang, Biao Zhang, Da Tang, Bolin Zhu, Yijie Zhu, Peng Wu, Ke Wang, Youlong Cheng | [https://arxiv.org/pdf/2209.07663.pdf](https://arxiv.org/pdf/2209.07663.pdf) | 2022 |", "2092550": "thanks for this short summary!" }, "source": "meta" }