Recommender System Papers

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Classic papers

• Matrix Factorization Techniques for Recommender Systems. Yehuda Koren, Robert M. Bell, Chris Volinsky. IEEE Computer 42(8): 30-37 (2009) [pdf]
• Factorization Machines with libFM. Steffen Rendle. ACM TIST 3(3): 57 (2012) [pdf]
• The recommender problem revisited: tutorial. Xavier Amatriain, Bamshad Mobasher. KDD 2014 [pdf]

Deep learning for modeling interactions

• 深度学习在推荐算法中的研究进展. 赵鑫. 中国人工智能学会通讯.2016年第七期. [pdf]
• Neural Collaborative Filtering. Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, Tat-Seng Chua. WWW 2017: 173-182 [pdf]
• A Neural Network Approach to Jointly Modeling Social Networks and Mobile Trajectories. Cheng Yang, Maosong Sun, Wayne Xin Zhao, Zhiyuan Liu, Edward Y. Chang. ACM Trans. Inf. Syst. 35(4): 36:1-36:28 (2017) [pdf]
• Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks. Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi. RecSys 2017: 130-137 [pdf]
• Neural Attentive Session-based Recommendation. Jing Li, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Tao Lian, Jun Ma. CIKM 2017: 1419-1428 [pdf]
• Self-Attentive Sequential Recommendation. Wang-Cheng Kang, Julian J. McAuley. ICDM 2018: 197-206 [pdf]
• BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer. Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou, Peng Jiang. CoRR abs/1904.06690 (2019) [pdf]

Deep learning for modeling context

• Deep Neural Networks for YouTube Recommendations. Paul Covington, Jay Adams, Emre Sargin. RecSys 2016: 191-19 [pdf]
• DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He. IJCAI 2017: 1725-1731 [pdf]
• Wide & Deep Learning for Recommender Systems. Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil, Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing Liu, Hemal Shah. DLRS@RecSys 2016: 7-10 [pdf]
• Learning deep structured semantic models for web search using clickthrough data. Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, Larry P. Heck. CIKM 2013: 2333-2338 [pdf]
• Collaborative Deep Learning for Recommender Systems. Hao Wang, Naiyan Wang, Dit-Yan Yeung. KDD 2015: 1235-1244 [pdf]
• Joint Deep Modeling of Users and Items Using Reviews for Recommendation. Lei Zheng, Vahid Noroozi, Philip S. Yu. WSDM 2017: 425-434 [pdf]
• Multi-Pointer Co-Attention Networks for Recommendation. Yi Tay, Anh Tuan Luu, Siu Cheung Hui. KDD 2018: 2309-2318 [pdf]
• A Review-Driven Neural Model for Sequential Recommendation. Chenliang Li, Xichuan Niu, Xiangyang Luo, Zhenzhong Chen, Cong Quan. IJCAI 2019: 2866-2872 [pdf]
• A Capsule Network for Recommendation and Explaining What You Like and Dislike. Chenliang Li, Cong Quan, Li Peng, Yunwei Qi, Yuming Deng, Libing Wu. SIGIR 2019: 275-284 [pdf]
• Deep content-based music recommendation. Aäron Van Den Oord, Sander Dieleman, Benjamin Schrauwen. NIPS 2013: 2643-2651 [pdf]
• A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems. Ali Mamdouh Elkahky, Yang Song, Xiaodong He. WWW 2015: 278-288 [pdf]
• A Collaborative Neural Model for Rating Prediction by Leveraging User Reviews and Product Images. Wenwen Ye, Yongfeng Zhang, Wayne Xin Zhao, Xu Chen, Zheng Qin. AIRS 2017: 99-111 [pdf]
• Aesthetic-based Clothing Recommendation. Wenhui Yu, Huidi Zhang, Xiangnan He, Xu Chen, Li Xiong, Zheng Qin. WWW 2018: 649-658 [pdf]

Interpretable recommendation

• Ripple Network:Propagating User Preferences on the Knowledge Graph for Recommender Systems. Hongwei Wang, Fuzheng Zhang, Jialin Wang, Miao Zhao, Wenjie Li, Xing Xie, Minyi Guo. 27th ACM International Conference on Information and Knowledge Management (CIKM 2018), Lingotto, Turin, Italy, Oct. 2018 [paper]
• Taxonomy-Aware Multi-Hop Reasoning Networks for Sequential Recommendation. Jin Huang, Zhaochun Ren, Wayne Xin Zhao, Gaole He, Ji-Rong Wen, Daxiang Dong. WSDM 2019: 573-581 [paper]
• Leveraging Meta-path based Context for Top-N Recommendation with A Neural Co-Attention Model. Binbin Hu, Chuan Shi, Wayne Xin Zhao, Philip S. Yu. KDD 2018: 1531-1540 [paper]
• KB4Rec: A Dataset for Linking Knowledge Bases with Recommender Systems. Wayne Xin Zhao, Gaole He, Hong-Jian Dou, Jin Huang, Siqi Ouyang, Ji-Rong Wen. CoRR abs/1807.11141 (2018) [paper] [code]
• TEM: Tree-enhanced Embedding Model for Explainable Recommendation. Xiang Wang, Xiangnan He, Fuli Feng, Liqiang Nie, Tat-Seng Chua. WWW 2018: 1543-1552 [paper]
• Collaborative Knowledge Base Embedding for Recommender Systems. Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, Wei-Ying Ma. KDD 2016: 353-362 [paper]

Reinforcement learning for recommendation

• Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning. Xiangyu Zhao, Liang Zhang, Zhuoye Ding, Long Xia, Jiliang Tang, Dawei Yin. KDD 2018: 1040-1048 [paper]
• DRN: A Deep Reinforcement Learning Framework for News Recommendation. Guanjie Zheng, Fuzheng Zhang, Zihan Zheng, Yang Xiang, Nicholas Jing Yuan, Xing Xie, Zhenhui Li. WWW 2018: 167-176 [paper]
• Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems. Lixin Zou, Long Xia, Zhuoye Ding, Jiaxing Song, Weidong Liu, Dawei Yin. KDD 2019: 2810-2818 [paper]
• Reinforcement Knowledge Graph Reasoning for Explainable Recommendation. Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard de Melo, Yongfeng Zhang. SIGIR 2019: 285-294 [paper]
• Deep reinforcement learning for page-wise recommendations. Xiangyu Zhao, Long Xia, Liang Zhang, Zhuoye Ding, Dawei Yin, Jiliang Tang. RecSys 2018: 95-103 [paper]

Interactive/conversational recommendation

• Towards Conversational Recommender Systems. Konstantina Christakopoulou, Filip Radlinski, Katja Hofmann. KDD 2016: 815-824 [paper]
• Local Representative-Based Matrix Factorization for Cold-Start Recommendation. Lei Shi, Wayne Xin Zhao, Yi-Dong Shen. ACM Trans. Inf. Syst. 36(2): 22:1-22:28 (2017) [paper]
• Conversational Recommender System. Yueming Sun, Yi Zhang. SIGIR 2018: 235-244 [paper]
• Towards Deep Conversational Recommendations. Raymond Li, Samira Ebrahimi Kahou, Hannes Schulz, Vincent Michalski, Laurent Charlin, Chris Pal. NeurIPS 2018: 9748-9758 [paper]
• Large-Scale Interactive Recommendation with Tree-Structured Policy Gradient. Haokun Chen, Xinyi Dai, Han Cai, Weinan Zhang, Xuejian Wang, Ruiming Tang, Yuzhou Zhang, Yong Yu. AAAI 2019: 3312-3320 [paper]

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