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Personalized news recommendation methods are widely used in online news services.
Embedding-based news recommendation for millions of users
Shumpei Okura, Yukihiro Tagami, Shingo Ono, and Akira Tajima. 2017 · 1942
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Ptum: Pre-training user model from unlabeled user behaviors via self-supervision
Chuhan Wu, Fangzhao Wu, Tao Qi, Jianxun Lian, Yongfeng Huang, and Xing Xie. 2020c · 1944
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
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Avoiding monotony: improving the diversity of recommendation lists
Mi Zhang and Neil Hurley. 2008 · 2008
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Using twitter to recommend real-time topical news
Owen Phelan, Kevin McCarthy, and Barry Smyth. 2009 · 2009
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Bpr: Bayesian personalized ranking from implicit feedback
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009 · 2009
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An approach to model and predict the popularity of online contents with explanatory factors
Jong Gun Lee, Sue Moon, and Kave Salamatian. 2010 · 2010
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Using a model of social dynamics to predict popularity of news
Kristina Lerman and Tad Hogg. 2010 · 2010
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Personalized news recommendation based on click behavior
Jiahui Liu, Peter Dolan, and Elin Rønby Pedersen. 2010 · 2010
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Predicting the popularity of online content
Gabor Szabo and Bernardo A Huberman. 2010 · 2010
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Do clicks measure recommendation relevancy? an empirical user study
Hua Zheng, Dong Wang, Qi Zhang, Hang Li, and Tinghao Yang. 2010 · 2010
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Scene: a scalable two-stage personalized news recommendation system
Lei Li, Dingding Wang, Tao Li, Daniel Knox, and Balaji Padmanabhan. 2011 · 2011
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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Cited alongside, same era.
Personalized news recommendation via implicit social experts
Chen Lin, Runquan Xie, Xinjun Guan, Lei Li, and Tao Li. 2014 · 2014
Cited alongside, same era.
Exploring the filter bubble: the effect of using recommender systems on content diversity
Tien T Nguyen, Pik-Mai Hui, F Maxwell Harper, Loren Terveen, and Joseph A Konstan. 2014 · 2014
Cited alongside, same era.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Cited alongside, same era.
Social collaborative filtering for cold-start recommendations
Suvash Sedhain, Scott Sanner, Darius Braziunas, Lexing Xie, and Jordan Christensen. 2014 · 2014
Cited alongside, same era.
From popularity prediction to ranking online news
Effects of popularity-based news recommendations (“most-viewed”) on users’ exposure to online news
JungAe Yang. 2016 · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Fast greedy map inference for determinantal point process to improve recommendation diversity
Laming Chen, Guoxin Zhang, and Eric Zhou. 2018 · 2018
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Dkn: Deep knowledge-aware network for news recommendation
Hongwei Wang, Fuzheng Zhang, Xing Xie, and Minyi Guo. 2018 · 2018
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Neural news recommendation with long-and short-term user representations
Mingxiao An, Fangzhao Wu, Chuhan Wu, Kun Zhang, Zheng Liu, and Xing Xie. 2019 · 2019
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The news we like are not the news we visit: news categories popularity in usage data
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Alexandru Tatar, Panayotis Antoniadis, Marcelo Dias De Amorim, and Serge Fdida. 2014 · 2014
Cited alongside, same era.
Cold-start news recommendation with domain-dependent browse graph
Michele Trevisiol, Luca Maria Aiello, Rossano Schifanella, and Alejandro Jaimes. 2014 · 2014
Cited alongside, same era.
Content driven user profiling for comment-worthy recommendations of news and blog articles
Trapit Bansal, Mrinal Das, and Chiranjib Bhattacharyya. 2015 · 2015
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2015 · 2015
Cited alongside, same era.
Research on ctr prediction for contextual advertising based on deep architecture model
Zilong Jiang. 2016 · 2016
Cited alongside, same era.
Incorporating popularity in a personalized news recommender system
Nirmal Jonnalagedda, Susan Gauch, Kevin Labille, and Sultan Alfarhood. 2016 · 2016
Cited alongside, same era.
Dealing with the new user cold-start problem in recommender systems: A comparative review
Le Hoang Son. 2016 · 2016
Cited alongside, same era.
Zied Ben Houidi, Giuseppe Scavo, Stefano Traverso, Renata Teixeira, Marco Mellia, and Soumen Ganguly. 2019 · 2019
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Dan: Deep attention neural network for news recommendation
Qiannan Zhu, Xiaofei Zhou, Zeliang Song, Jianlong Tan, and Guo Li. 2019 · 2019
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Graph enhanced representation learning for news recommendation
Suyu Ge, Chuhan Wu, Fangzhao Wu, Tao Qi, and Yongfeng Huang. 2020 · 2020
Later among the works it cites.
A re-visit of the popularity baseline in recommender systems
Yitong Ji, Aixin Sun, Jie Zhang, and Chenliang Li. 2020 · 2020
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Kred: Knowledge-aware document representation for news recommendations
Danyang Liu, Jianxun Lian, Shiyin Wang, Ying Qiao, Jiun-Hung Chen, Guangzhong Sun, and Xing Xie. 2020 · 2020
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Privacy-preserving news recommendation model learning
Tao Qi, Fangzhao Wu, Chuhan Wu, Yongfeng Huang, and Xing Xie. 2020 · 2020
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Fairrec:fairness-aware news recommendation with decomposed adversarial learning
Chuhan Wu, Fangzhao Wu, Xiting Wang, Yongfeng Huang, and Xing Xie. 2021 · 2021
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