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Recommender Systems have proliferated as general-purpose approaches to model a wide variety of consumer interaction data.
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Translating embeddings for modeling multi-relational data. In NIPS’13
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Beyond clicks: dwell time for personalization. In RecSys’14
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Personalized entity recommendation: A heterogeneous information network approach. In WSDM’14
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Personalized ranking metric embedding for next new POI recommendation. In IJCAI’15
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Learning Entity and Relation Embeddings for Knowledge Graph Completion. In AAAI’15
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Autorec: Autoencoders meet collaborative filtering. In WWW’15
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Collaborative Deep Learning for Recommender Systems. In KDD’15
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Generating and Personalizing Bundle Recommendations on Steam . In SIGIR’17
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Interacting Attention-gated Recurrent Networks for Recommendation. In CIKM’17
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Contextual Sequence Modeling for Recommendation with Recurrent Neural Networks. In DLRS@RecSys’17
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Fusing similarity models with markov chains for sparse sequential recommendation. In ICDM’16
Ruining He and Julian McAuley. 2016 · 2016
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Session-based Recommendations with Recurrent Neural Networks. In ICLR’16
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Convolutional Matrix Factorization for Document Context-Aware Recommendation. In RecSys’16
Dong Hyun Kim, Chanyoung Park, Jinoh Oh, Sungyoung Lee, and Hwanjo Yu. 2016 · 2016
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Collaborative Knowledge Base Embedding for Recommender Systems. In KDD’16
Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, and Wei-Ying Ma. 2016 · 2016
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Recurrent Neural Networks with Top-k Gains for Session-based Recommendations
Balázs Hidasi and Alexandros Karatzoglou. 2017 · 2017
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Collaborative Metric Learning. In WWW’17
Cheng-Kang Hsieh, Longqi Yang, Yin Cui, Tsung-Yi Lin, Serge J. Belongie, and Deborah Estrin. 2017 · 2017
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Neural Survival Recommender. In WSDM’17
How Jing and Alexander J. Smola. 2017 · 2017
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Modeling the evolution of users’ preferences and social links in social networking services
Le Wu, Yong Ge, Qi Liu, Enhong Chen, Richang Hong, Junping Du, and Meng Wang. 2017 · 2017
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Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI Recommendation. In KDD’17
Carl Yang, Lanxiao Bai, Chao Zhang, Quan Yuan, and Jiawei Han. 2017 · 2017
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Deep Learning based Recommender System: A Survey and New Perspectives
Shuai Zhang, Lina Yao, and Aixin Sun. 2017 · 2017
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Meta-graph based recommendation fusion over heterogeneous information networks. In KDD’17
Huan Zhao, Quanming Yao, Jianda Li, Yangqiu Song, and Dik Lun Lee. 2017 · 2017
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Latent Cross: Making Use of Context in Recurrent Recommender Systems. In WSDM’18
Alex Beutel, Paul Covington, Sagar Jain, Can Xu, Jia Li, Vince Gatto, and Ed H Chi. 2018 · 2018
Closest in time.
TransRev: Modeling Reviews as Translations from Users to Items
Alberto Garcia-Duran, Roberto Gonzalez, Daniel Onoro-Rubio, Mathias Niepert, and Hui Li. 2018 · 2018
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Crossfire: Cross media joint friend and item recommendations. In WSDM’18
Kai Shu, Suhang Wang, Jiliang Tang, Yilin Wang, and Huan Liu. 2018 · 2018
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Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding. In WSDM’18
Jiaxi Tang and Ke Wang. 2018 · 2018
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Latent Relational Metric Learning via Memory-based A ention for Collaborative Ranking. In WWW’18
Yi Tay, Luu Anh Tuan, and Siu Cheung Hui. 2018 · 2018
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