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Recommender systems are ubiquitous in the domain of e-commerce, used to improve the user experience and to market inventory, thereby increasing revenue for the site.
Tag-Aware Personalized Recommendation Using a Deep-Semantic Similarity Model with Negative Sampling. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management
Zhenghua Xu, Cheng Chen, Thomas Lukasiewicz, Yishu Miao, and Xiangwu Meng. 2016 · 1924
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Probabilistic Models for Unified Collaborative and Content-based Recommendation in Sparse-data Environments. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence
Alexandrin Popescul, David M. Pennock, and Steve Lawrence. 2001 · 2001
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Hybrid Recommender Systems: Survey and Experiments
Robin Burke. 2002 · 2002
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Content-boosted Collaborative Filtering for Improved Recommendations. In Eighteenth National Conference on Artificial Intelligence
Prem Melville, Raymod J. Mooney, and Ramadass Nagarajan. 2002 · 2002
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An Approach for Combining Content-based and Collaborative Filters. In Proceedings of the Sixth International Workshop on Information Retrieval with Asian Languages - Volume 11
Qing Li and Byeong Man Kim. 2003 · 2003
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Amazon. com recommendations: Item-to-item collaborative filtering
Greg Linden, Brent Smith, and Jeremy York. 2003 · 2003
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Unifying Collaborative and Content-based Filtering. In Proceedings of the Twenty-first International Conference on Machine Learning
Justin Basilico and Thomas Hofmann. 2004 · 2004
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Item-based top-N Recommendation Algorithms
Mukund Deshpande and George Karypis. 2004 · 2004
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Collaborative Filtering for Implicit Feedback Datasets. In Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Yifan Hu, Yehuda Koren, and Chris Volinsky. 2008 · 2008
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Probabilistic Matrix Factorization. In Advances in Neural Information Processing Systems
Ruslan Salakhutdinov and Andriy Mnih. 2008 · 2008
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Matrix Factorization Techniques for Recommender Systems
Yehuda Koren, Robert Bell, and Chris Volinsky. 2009 · 2009
Cited alongside, same era.
Recommender Systems: An Introduction
Dietmar Jannach, Markus Zanker, Alexander Felfernig, and Gerhard Friedrich. 2010 · 2010
Cited alongside, same era.
Content-based Recommender Systems: State of the Art and Trends
Pasquale Lops, Marco de Gemmis, and Giovanni Semeraro. 2011 · 2011
Cited alongside, same era.
Learning Deep Structured Semantic Models for Web Search Using Clickthrough Data. In Proceedings of the 22Nd ACM International Conference on Information & Knowledge Management
Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, and Larry Heck. 2013 · 2013
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A Deep Architecture for Matching Short Texts
Zhengdong Lu and Hang Li. 2013 · 2013
Cited alongside, same era.
Efficient Estimation of Word Representations in Vector Space
A Probabilistic Rating Auto-encoder for Personalized Recommender Systems. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management
Huizhi Liang and Timothy Baldwin. 2015 · 2015
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Image-Based Recommendations on Styles and Substitutes. In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
Julian McAuley, Christopher Targett, Qinfeng Shi, and Anton van den Hengel. 2015 · 2015
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Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks. In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
Aliaksei Severyn and Alessandro Moschitti. 2015 · 2015
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Character-level Convolutional Networks for Text Classification. In Proceedings of the 28th International Conference on Neural Information Processing Systems
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013a · 2013
Cited alongside, same era.
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Junyoung Chung, Çaglar Gülçehre, KyungHyun Cho, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Recommending Music on Spotify with Deep Learning
Sander Dieleman. 2014 · 2014
Cited alongside, same era.
A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval. In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management
Yelong Shen, Xiaodong He, Jianfeng Gao, Li Deng, and Grégoire Mesnil. 2014 · 2014
Cited alongside, same era.
Visual Search at Pinterest. In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Yushi Jing, David Liu, Dmitry Kislyuk, Andrew Zhai, Jiajing Xu, Jeff Donahue, and Sarah Tavel. 2015 · 2015
Cited alongside, same era.
Deep Neural Networks for YouTube Recommendations. In Proceedings of the 10th ACM Conference on Recommender Systems
Paul Covington, Jay Adams, and Emre Sargin. 2016a
Cited in the paper.
Bhaskar Mitra, Fernando Diaz, and Nick Craswell. 2016 · 2016
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Theano: A Python framework for fast computation of mathematical expressions
Theano Development Team. 2016 · 2016
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Retweet Prediction with Attention-based Deep Neural Network. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management
Qi Zhang, Yeyun Gong, Jindou Wu, Haoran Huang, and Xuanjing Huang. 2016 · 2016
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Tag-aware Recommender Systems Based on Deep Neural Networks
Yi Zuo, Jiulin Zeng, Maoguo Gong, and Licheng Jiao. 2016 · 2016
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Match-Tensor: a Deep Relevance Model for Search
Aaron Jaech, Hetunandan Kamisetty, Eric K. Ringger, and Charlie Clarke. 2017 · 2017
Later among the works it cites.
Convolutional Neural Network Architectures for Matching Natural Language Sentences
Baotian Hu, Zhengdong Lu, Hang Li, and Qingcai Chen. 2014 · 2050
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