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This paper proposes Medley of Sub-Attention Networks (MoSAN), a new novel neural architecture for the group recommendation task.
Embedding-based News Recommendation for Millions of Users. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13 - 17, 2017 . 1933–1942
Shumpei Okura, Yukihiro Tagami, Shingo Ono, and Akira Tajima. 2017 · 1942
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Dropout: a simple way to prevent neural networks from overfitting
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PolyLens: A recommender system for groups of user. In Proceedings of the Seventh European Conference on Computer Supported Cooperative Work, 16-20 September 2001, Bonn, Germany . 199–218
Mark O’Connor, Dan Cosley, Joseph A. Konstan, and John Riedl. 2001 · 2001
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CATS: A Synchronous Approach to Collaborative Group Recommendation. In Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, Melbourne Beach, Florida, USA, May 11-13, 2006 . 86–91
Kevin McCarthy, Maria Salamó, Lorcan Coyle, Lorraine McGinty, Barry Smyth, and Paddy Nixon. 2006 · 2006
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TV Program Recommendation for Multiple Viewers Based on user Profile Merging
Zhiwen Yu, Xingshe Zhou, Yanbin Hao, and Jianhua Gu. 2006 · 2006
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Group Recommendation: Semantics and Efficiency
Sihem Amer-Yahia, Senjuti Basu Roy, Ashish Chawla, Gautam Das, and Cong Yu. 2009 · 2009
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Matrix Factorization Techniques for Recommender Systems
Yehuda Koren, Robert Bell, and Chris Volinsky. 2009 · 2009
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BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI 2009, Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, Montreal, QC, Canada, June 18-21, 2009 . 452–461
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A Survey of Collaborative Filtering Techniques
Xiaoyuan Su and Taghi M. Khoshgoftaar. 2009 · 2009
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fLDA: matrix factorization through latent dirichlet allocation. In Proceedings of the Third International Conference on Web Search and Web Data Mining, WSDM 2010, New York, NY, USA, February 4-6, 2010 . 91–100
Deepak Agarwal and Bee-Chung Chen. 2010 · 2010
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Group recommendations with rank aggregation and collaborative filtering. In Proceedings of the 2010 ACM Conference on Recommender Systems, RecSys 2010, Barcelona, Spain, September 26-30, 2010 . 119–126
Linas Baltrunas, Tadas Makcinskas, and Francesco Ricci. 2010 · 2010
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Group-based recipe recommendations: analysis of data aggregation strategies. In Proceedings of the 2010 ACM Conference on Recommender Systems, RecSys 2010, Barcelona, Spain, September 26-30, 2010 . 111–118
Shlomo Berkovsky and Jill Freyne. 2010 · 2010
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State-of-the-Art in Group Recommendation and New Approaches for Automatic Identification of Groups
Ludovico Boratto and Salvatore Carta. 2011 · 2011
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Group recommendation using feature space representing behavioral tendency and power balance among members. In Proceedings of the 2011 ACM Conference on Recommender Systems, RecSys 2011, Chicago, IL, USA, October 23-27, 2011 . 101–108
Shunichi Seko, Takashi Yagi, Manabu Motegi, and Shin-yo Muto. 2011 · 2011
Cited alongside, same era.
Collaborative topic modeling for recommending scientific articles. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, August 21-24, 2011 . 448–456
Chong Wang and David M. Blei. 2011 · 2011
Cited alongside, same era.
Event-based social networks: linking the online and offline social worlds. In The 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’12, Beijing, China, August 12-16, 2012 . 1032–1040
Xingjie Liu, Qi He, Yuanyuan Tian, Wang-Chien Lee, John McPherson, and Jiawei Han. 2012a · 2012
Cited alongside, same era.
Exploring personal impact for group recommendation. In 21st ACM International Conference on Information and Knowledge Management, CIKM’12, Maui, HI, USA, October 29 - November 02, 2012 . 674–683
Deep Neural Networks for YouTube Recommendations. In Proceedings of the 10th ACM Conference on Recommender Systems, Boston, MA, USA, September 15-19, 2016 . 191–198
Paul Covington, Jay Adams, and Emre Sargin. 2016 · 2016
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A General Recommendation Model for Heterogeneous Networks
Tuan-Anh Nguyen Pham, Xutao Li, Gao Cong, and Zhenjie Zhang. 2016 · 2016
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Recommending New Items to Ephemeral Groups Using Contextual User Influence. In Proceedings of the 10th ACM Conference on Recommender Systems (RecSys ’16)
Elisa Quintarelli, Emanuele Rabosio, and Letizia Tanca. 2016 · 2016
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Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, Shinjuku, Tokyo, Japan, August 7-11, 2017 . 335–344
Jingyuan Chen, Hanwang Zhang, Xiangnan He, Liqiang Nie, Wei Liu, and Tat-Seng Chua. 2017 · 2017
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Xingjie Liu, Yuan Tian, Mao Ye, and Wang-Chien Lee. 2012b · 2012
Cited alongside, same era.
Exploring social influence for recommendation: a generative model approach. In The 35th International ACM SIGIR conference on research and development in Information Retrieval, SIGIR ’12, Portland, OR, USA, August 12-16, 2012 . 671–680
Mao Ye, Xingjie Liu, and Wang-Chien Lee. 2012 · 2012
Cited alongside, same era.
Users’ satisfaction in recommendation systems for groups: an approach based on noncooperative games. In 22nd International World Wide Web Conference, WWW ’13, Rio de Janeiro, Brazil, May 13-17, 2013, Companion Volume . 951–958
Lucas Augusto Montalvão Costa Carvalho and Hendrik Teixeira Macedo. 2013 · 2013
Cited alongside, same era.
Probabilistic group recommendation via information matching. In 22nd International World Wide Web Conference, WWW ’13, Rio de Janeiro, Brazil, May 13-17, 2013 . 495–504
Jagadeesh Gorla, Neal Lathia, Stephen Robertson, and Jun Wang. 2013 · 2013
Cited alongside, same era.
Deep Modeling of Group Preferences for Group-Based Recommendation. In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27 -31, 2014, Québec City, Québec, Canada. 1861–1867
Liang Hu, Jian Cao, Guandong Xu, Longbing Cao, Zhiping Gu, and Wei Cao. 2014 · 2014
Cited alongside, same era.
COM: a generative model for group recommendation. In The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’14, New York, NY, USA - August 24 - 27, 2014 . 163–172
Quan Yuan, Gao Cong, and Chin-Yew Lin. 2014 · 2014
Cited alongside, same era.
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
Cited alongside, same era.
Attention-Based Models for Speech Recognition. In Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada . 577–585
Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
Cited alongside, same era.
Show and tell: A neural image caption generator. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, June 7-12, 2015 . 3156–3164
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan. 2015 · 2015
Cited alongside, same era.
Neural Collaborative Filtering. In Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Perth, Australia, April 3-7, 2017 . 173–182
Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua. 2017 · 2017
Later among the works it cites.
Attention is All you Need. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 4-9 December 2017, Long Beach, CA, USA . 6000–6010
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Later among the works it cites.
Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI’17) . AAAI Press, 3119–3125
Jun Xiao, Hao Ye, Xiangnan He, Hanwang Zhang, Fei Wu, and Tat-Seng Chua. 2017 · 2017
Later among the works it cites.
Attentive Group Recommendation. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR ’18) . ACM, New York, NY, USA, 645–654
Da Cao, Xiangnan He, Lianhai Miao, Yahui An, Chao Yang, and Richang Hong. 2018 · 2018
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ANR: Aspect-based Neural Recommender. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, October 22-26, 2018 . 147–156
Jin Yao Chin, Kaiqi Zhao, Shafiq R. Joty, and Gao Cong. 2018 · 2018
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Multi-Pointer Co-Attention Networks for Recommendation. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2018, London, UK, August 19-23, 2018 . 2309–2318
Yi Tay, Anh Tuan Luu, and Siu Cheung Hui. 2018 · 2018
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Deep Learning Based Recommender System: A Survey and New Perspectives
Shuai Zhang, Lina Yao, Aixin Sun, and Yi Tay. 2019 · 2019
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