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Keyword

implicit feedback

Description: Information about user preferences inferred from behavior, such as choices or interactions, rather than directly stated ratings.
OpenAlex ID: keywords/implicit-feedback
Matrix Factorization Techniques for Recommender Systems
2009 · Yehuda Koren, Robert Bell, et al. · Computer · 11,699
Neural Collaborative Filtering
2017 · Xiangnan He, Lizi Liao, et al. · International World Wide Web Conference (WWW) · 7,055
BPR: Bayesian Personalized Ranking from Implicit Feedback
2012 · Rendle, Steffen, Freudenthaler, Christoph, et al. · arXiv (Cornell University) · 4,603
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Collaborative Filtering for Implicit Feedback Datasets
2008 · Yifan Hu, Yehuda Koren, et al. · Proceedings · 3,246
Recommender systems survey
2013 · J. Bobadilla, F. Ortega, et al. · Knowledge-Based Systems · 3,165
Accurately interpreting clickthrough data as implicit feedback
2005 · Thorsten Joachims, Laura Granka, et al. · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · 1,395
Variational Autoencoders for Collaborative Filtering
2018 · Dawen Liang, Rahul G. Krishnan, et al. · 1,386
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Implicit and Explicit Corrective Feedback and the Acquisition of L2 Grammar
2006 · Rod Ellis, Shawn Loewen, et al. · Studies in Second Language Acquisition · 1,075
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Improving web search ranking by incorporating user behavior information
2006 · Eugene Agichtein, Eric Brill, et al. · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · 1,043
VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback
2016 · Ruining He, Julian McAuley · Proceedings of the AAAI Conference on Artificial Intelligence · 1,027
Fast Matrix Factorization for Online Recommendation with Implicit Feedback
2016 · Xiangnan He, Hanwang Zhang, et al. · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · 1,023
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Deep Matrix Factorization Models for Recommender Systems
2017 · Hong-Jian Xue, Xinyu Dai, et al. · International Joint Conference on Artificial Intelligence · 982
The Effectiveness of Corrective Feedback in SLA: A Meta‐Analysis
2010 · Shaofeng Li · Language Learning · 940
Advances in Collaborative Filtering
2010 · Yehuda Koren, Robert Bell · Springer eBooks · 853
Attentive Collaborative Filtering
2017 · Jingyuan Chen, Hanwang Zhang, et al. · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · 851
Implicit feedback for inferring user preference
2003 · Diane Kelly, Jaime Teevan · ACM SIGIR Forum · 743
Eye-tracking analysis of user behavior in WWW search
2004 · Laura A. Granka, Thorsten Joachims, et al. · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · 701
Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search
2007 · Thorsten Joachims, Laura Granka, et al. · ACM Transactions on Information Systems · 678
GeoMF
2014 · Defu Lian, Cong Zhao, et al. · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 609
On social networks and collaborative recommendation
2009 · Ioannis Konstas, Vassilios Stathopoulos, et al. · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · 608
Explicit and Implicit Negative Feedback
1993 · Susanne Carroll, Merrill Swain · Studies in Second Language Acquisition · 542
A dynamic bayesian network click model for web search ranking
2009 · Olivier Chapelle, Ya Zhang · International World Wide Web Conference (WWW) · 537
Unbiased Learning-to-Rank with Biased Feedback
2017 · Thorsten Joachims, Adith Swaminathan, et al. · ACM International Conference on Web Search and Data Mining (WSDM) · 527
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Advances in Collaborative Filtering
2015 · Yehuda Koren, Robert Bell · Springer eBooks · 497
User Modeling for Adaptive News Access
2000 · Daniel Billsus, Michael J. Pazzani · User Modeling and User-Adapted Interaction · 488
Works count: 3,554
Citation count: 98,020
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