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Next Point-of-Interest (POI) recommendation is of great value for both location-based service providers and users.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Factorizing personalized markov chains for next-basket recommendation
Steffen Rendle, Christoph Freudenthaler, and Lars Schmidt-Thieme · 2010
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Exploiting geographical influence for collaborative point-of-interest recommendation
Mao Ye, Peifeng Yin, Wang-Chien Lee, and Dik-Lun Lee · 2011
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gscorr: modeling geo-social correlations for new check-ins on location-based social networks
Huiji Gao, Jiliang Tang, and Huan Liu · 2012
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Making gradient descent optimal for strongly convex stochastic optimization
Alexander Rakhlin, Ohad Shamir, and Karthik Sridharan · 2012
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Where you like to go next: Successive point-of-interest recommendation
Chen Cheng, Haiqin Yang, Michael R Lyu, and Irwin King · 2013
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Geo topic model: joint modeling of user’s activity area and interests for location recommendation
Takeshi Kurashima, Tomoharu Iwata, Takahide Hoshide, Noriko Takaya, and Ko Fujimura · 2013
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Time-aware point-of-interest recommendation
Quan Yuan, Gao Cong, Zongyang Ma, Aixin Sun, and Nadia Magnenat Thalmann · 2013
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Learning phrase representations using RNN encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Geomf: joint geographical modeling and matrix factorization for point-of-interest recommendation
Defu Lian, Cong Zhao, Xing Xie, Guangzhong Sun, Enhong Chen, and Yong Rui · 2014
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Improving content-based and hybrid music recommendation using deep learning
Xinxi Wang and Ye Wang · 2014
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Sequential click prediction for sponsored search with recurrent neural networks
Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, and Tie-Yan Liu · 2014
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Personalized ranking metric embedding for next new poi recommendation
Shanshan Feng, Xutao Li, Yifeng Zeng, Gao Cong, Yeow Meng Chee, and Quan Yuan · 2015
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Session-based recommendations with recurrent neural networks
Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk · 2015
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Learning graph-based poi embedding for location-based recommendation
Min Xie, Hongzhi Yin, Hao Wang, Fanjiang Xu, Weitong Chen, and Sen Wang · 2016
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Collaborative knowledge base embedding for recommender systems
Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, and Wei-Ying Ma · 2016
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A neural autoregressive approach to collaborative filtering
Yin Zheng, Bangsheng Tang, Wenkui Ding, and Hanning Zhou · 2016
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LSTM: A search space odyssey
Klaus Greff, Rupesh Kumar Srivastava, Jan Koutník, Bas R. Steunebrink, and Jürgen Schmidhuber · 2017
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Bridging collaborative filtering and semi-supervised learning: A neural approach for poi recommendation
Carl Yang, Lanxiao Bai, Chao Zhang, Quan Yuan, and Jiawei Han · 2017
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A neural network approach to jointly modeling social networks and mobile trajectories
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Adaptation and evaluation of recommendations for short-term shopping goals
Dietmar Jannach, Lukas Lerche, and Michael Jugovac · 2015
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Inferring a personalized next point-of-interest recommendation model with latent behavior patterns
Jing He, Xin Li, Lejian Liao, Dandan Song, and William K Cheung · 2016
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Predicting the next location: A recurrent model with spatial and temporal contexts
Qiang Liu, Shu Wu, Liang Wang, and Tieniu Tan · 2016
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Unified point-of-interest recommendation with temporal interval assessment
Yanchi Liu, Chuanren Liu, Bin Liu, Meng Qu, and Hui Xiong · 2016
Cited alongside, same era.
Cheng Yang, Maosong Sun, Wayne Xin Zhao, Zhiyuan Liu, and Edward Y. Chang · 2017
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Next: A neural network framework for next poi recommendation
Zhiqian Zhang, Chenliang Li, Zhiyong Wu, Aixin Sun, Dengpan Ye, and Xiangyang Luo · 2017
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What to do next: Modeling user behaviors by time-lstm
Yu Zhu, Hao Li, Yikang Liao, Beidou Wang, Ziyu Guan, Haifeng Liu, and Deng Cai · 2017
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