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Click-Through Rate (CTR) prediction plays an important role in many industrial applications, such as online advertising and recommender systems.
Long short-term memory
Sepp Hochreiter and Jrgen Schmidhuber · 1997
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Item-based collaborative filtering recommendation algorithms
Badrul Munir Sarwar, George Karypis, Joseph A Konstan, John Riedl, et al · 2001
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Framewise phoneme classification with bidirectional lstm and other neural network architectures
Alex Graves and Jrgen Schmidhuber · 2005
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2014
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Session-based recommendations with recurrent neural networks
Balzs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk · 2015
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Wide & deep learning for recommender systems
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Deep neural networks for youtube recommendations
Covington, Paul, Adams, Jay, Sargin, and Emre · 2016
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General factorization framework for context-aware recommendations
Balzs Hidasi and Domonkos Tikk · 2016
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Parallel recurrent neural network architectures for feature-rich session-based recommendations
Balázs Hidasi, Massimo Quadrana, Alexandros Karatzoglou, and Domonkos Tikk · 2016
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Deepfm: a factorization-machine based neural network for ctr prediction
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Neural attentive session-based recommendation
Jing Li, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Tao Lian, and Jun Ma · 2017
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Personalizing session-based recommendations with hierarchical recurrent neural networks
Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, and Paolo Cremonesi · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, ukasz Kaiser, and Illia Polosukhin · 2017
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Real-time personalization using embeddings for search ranking at airbnb
Mihajlo Grbovic and Haibin Cheng · 2018
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Self-attentive sequential recommendation
Wang-Cheng Kang and Julian McAuley · 2018
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Learning from history and present: Next-item recommendation via discriminatively exploiting user behaviors
Zhi Li, Hongke Zhao, Qi Liu, Zhenya Huang, Tao Mei, and Enhong Chen · 2018
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Stamp: short-term attention/memory priority model for session-based recommendation
Qiao Liu, Yifu Zeng, Refuoe Mokhosi, and Haibin Zhang · 2018
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Personalized top-n sequential recommendation via convolutional sequence embedding
Jiaxi Tang and Ke Wang · 2018
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Atrank: An attention-based user behavior modeling framework for recommendation
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Deep & cross network for ad click predictions
Ruoxi Wang, Bin Fu, Gang Fu, and Mingliang Wang · 2017
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Jun Xiao, Hao Ye, Xiangnan He, Hanwang Zhang, Fei Wu, and Tat-Seng Chua · 2017
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Sequential recommendation with user memory networks
Xu Chen, Hongteng Xu, Yongfeng Zhang, Jiaxi Tang, Yixin Cao, Zheng Qin, and Hongyuan Zha · 2018
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Chang Zhou, Jinze Bai, Junshuai Song, Xiaofei Liu, Zhengchao Zhao, Xiusi Chen, and Jun Gao · 2018
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Deep interest evolution network for click-through rate prediction
Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, and Kun Gai · 2018
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Deep interest network for click-through rate prediction
Guorui Zhou, Xiaoqiang Zhu, Chenru Song, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, and Kun Gai · 2018
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