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Recommender systems are critical tools to match listings and travelers in two-sided vacation rental marketplaces.
Chu Wang, Lei Tang, Shujun Bian, Da Zhang, Zuohua Zhang, and Yongning Wu. 2019b · 1904
Earlier work this paper cites.
Probabilistic matrix factorization. In Advances in neural information processing systems . 1257–1264
Andriy Mnih and Ruslan R Salakhutdinov. 2008 · 2008
Earlier work this paper cites.
Testing models of consumer search using data on web browsing and purchasing behavior
Babur De los Santos, Ali Hortaçsu, and Matthijs R Wildenbeest. 2012 · 2012
Earlier work this paper cites.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
Earlier work this paper cites.
Logistic matrix factorization for implicit feedback data
Christopher C Johnson. 2014 · 2014
Earlier work this paper cites.
TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng. 2015 · 2015
Earlier work this paper cites.
E-commerce in your inbox: Product recommendations at scale. In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . ACM, 1809–1818
Mihajlo Grbovic, Vladan Radosavljevic, Nemanja Djuric, Narayan Bhamidipati, Jaikit Savla, Varun Bhagwan, and Doug Sharp. 2015 · 2015
Earlier work this paper cites.
Deep unordered composition rivals syntactic methods for text classification. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) , Vol. 1. 1681–1691
Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, and Hal Daumé III. 2015 · 2015
Earlier work this paper cites.
Autorec: Autoencoders meet collaborative filtering. In Proceedings of the 24th International Conference on World Wide Web . ACM, 111–112
Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, and Lexing Xie. 2015 · 2015
Earlier work this paper cites.
A simple but tough-to-beat baseline for sentence embeddings
Sanjeev Arora, Yingyu Liang, and Tengyu Ma. 2016 · 2016
Cited alongside, same era.
Factorization meets the item embedding: Regularizing matrix factorization with item co-occurrence. In Proceedings of the 10th ACM conference on recommender systems . ACM, 59–66
Dawen Liang, Jaan Altosaar, Laurent Charlin, and David M Blei. 2016 · 2016
Cited alongside, same era.
Apache Spark: a unified engine for big data processing
Matei Zaharia, Reynold Xin, Patrick Wendell, Tathagata Das, Michael Armbrust, Ankur Dave, Xiangrui Meng, Josh Rosen, Shivaram Venkataraman, Michael J. Franklin, Ali Ghodsi, Joseph Gonzalez, Scott Shenker, and Ion Stoica. 2016 · 2016
Cited alongside, same era.
Attention-based bidirectional long short-term memory networks for relation classification. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) , Vol. 2. 207–212
Peng Zhou, Wei Shi, Jun Tian, Zhenyu Qi, Bingchen Li, Hongwei Hao, and Bo Xu. 2016 · 2016
Cited alongside, same era.
Predicting Purchasing Intent: Automatic Feature Learning using Recurrent Neural Networks
Humphrey Sheil, Omer Rana, and Ronan G. Reilly. 2018 · 2018
Later among the works it cites.
Session-based Recommendation with Graph Neural Networks
Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, and Tieniu Tan. 2018 · 2018
Later among the works it cites.
Han Zhu, Xiang Li, Pengye Zhang, Guozheng Li, Jie He, Han Li, and Kun Gai. 2018 · 2018
Later among the works it cites.
An Attentive Survey of Attention Models
Sneha Chaudhari, Gungor Polatkan, Rohan Ramanath, and Varun Mithal. 2019 · 2019
Closest in time.
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Veronika Bogina and Tsvi Kuflik. 2017 · 2017
Cited alongside, same era.
Sorting through search and matching models in economics
Hector Chade, Jan Eeckhout, and Lones Smith. 2017 · 2017
Cited alongside, same era.
Understanding consumer behavior with recurrent neural networks. In Workshop on Machine Learning Methods for Recommender Systems
Tobias Lang and Matthias Rettenmeier. 2017 · 2017
Cited alongside, same era.
Word2vec applied to recommendation: Hyperparameters matter. In Proceedings of the 12th ACM Conference on Recommender Systems . ACM, 352–356
Hugo Caselles-Dupré, Florian Lesaint, and Jimena Royo-Letelier. 2018 · 2018
Cited alongside, same era.
Deep neural network marketplace recommenders in online experiments. In Proceedings of the 12th ACM Conference on Recommender Systems . ACM, 387–391
Simen Eide and Ning Zhou. 2018 · 2018
Cited alongside, same era.
Thom Lake, Sinead A Williamson, Alexander T Hawk, Christopher C Johnson, and Benjamin P Wing. 2019 · 2019
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Yuan Xia, Jingbo Zhou, Jingjia Cao, Yanyan Li, Fei Gao, Kun Liu, Haishan Wu, and Hui Xiong. 2019 · 2019
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