Filip Radlinski

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Coauteurs

Thorsten JoachimsProfessor of Computer Science, Cornell UniversityAdresse e-mail validée de cs.cornell.edu
Nick CraswellMicrosoftAdresse e-mail validée de microsoft.com
Krisztian BalogUniversity of Stavanger & Google DeepMindAdresse e-mail validée de uis.no
Katja HofmannMicrosoft ResearchAdresse e-mail validée de microsoft.com
Milad ShokouhiMicrosoftAdresse e-mail validée de microsoft.com
Paul N. BennettDirector of Research, Large Language Models, SpotifyAdresse e-mail validée de spotify.com
Emine YilmazUniversity College LondonAdresse e-mail validée de ucl.ac.uk
Yisong YueCalifornia Institute of Technology; Asari AI; Latitude AIAdresse e-mail validée de caltech.edu
Ryen W. WhiteGeneral Manager, Deputy Lab Director, Microsoft ResearchAdresse e-mail validée de microsoft.com
Laura GrankaGoogle, IncAdresse e-mail validée de google.com
Susan DumaisTechnical Fellow, Microsoft ResearchAdresse e-mail validée de microsoft.com
Robert KleinbergDepartment of Computer Science, Cornell UniversityAdresse e-mail validée de cs.cornell.edu
Hamed ZamaniAssociate Professor of Computer Science, University of Massachusetts AmherstAdresse e-mail validée de cs.umass.edu
Aleksandrs SlivkinsSenior Principal Researcher, Microsoft Research NYCAdresse e-mail validée de microsoft.com
Madhu KurupVice PresidentAdresse e-mail validée de amazon.com
Geri GayProfessor of Information Science and Communication, Cornell UniversityAdresse e-mail validée de cornell.edu
Bing PanPenn State UniversityAdresse e-mail validée de psu.edu
Johanne R. TrippasVice-Chancellor's Research Fellow, School of Computing Technologies, RMIT UniversityAdresse e-mail validée de rmit.edu.au
Jeff DaltonAssociate Professor (Reader) at University of EdinburghAdresse e-mail validée de ed.ac.uk
Sreenivas GollapudiGoogleAdresse e-mail validée de google.com

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Filip Radlinski

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Information Retrieval Machine Learning


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
A support vector method for optimizing average precision Y Yue, T Finley, F Radlinski, T Joachims Proceedings of the 30th annual international ACM SIGIR conference on …, 2007	919	2007
Evaluating the accuracy of implicit feedback from clicks and query reformulations in web search T Joachims, L Granka, B Pan, H Hembrooke, F Radlinski, G Gay ACM Transactions on Information Systems (TOIS) 25 (2), 7-es, 2007	828	2007
Query chains: learning to rank from implicit feedback F Radlinski, T Joachims Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005	701	2005
Learning diverse rankings with multi-armed bandits F Radlinski, R Kleinberg, T Joachims Proceedings of the 25th international conference on Machine learning, 784-791, 2008	615	2008
Towards conversational recommender systems K Christakopoulou, F Radlinski, K Hofmann Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016	497	2016
A theoretical framework for conversational search F Radlinski, N Craswell Proceedings of the 2017 conference on conference human information …, 2017	443	2017
How does clickthrough data reflect retrieval quality? F Radlinski, M Kurup, T Joachims Proceedings of the 17th ACM conference on Information and knowledge …, 2008	414	2008
Improving personalized web search using result diversification F Radlinski, S Dumais Proceedings of the 29th annual international ACM SIGIR conference on …, 2006	351	2006
Personalizing web search using long term browsing history N Matthijs, F Radlinski Proceedings of the fourth ACM international conference on Web search and …, 2011	281	2011
Search engines that learn from implicit feedback T Joachims, F Radlinski Computer 40 (8), 34-40, 2007	253	2007
Large-scale validation and analysis of interleaved search evaluation O Chapelle, T Joachims, F Radlinski, Y Yue ACM Transactions on Information Systems (TOIS) 30 (1), 1-41, 2012	231	2012
Active exploration for learning rankings from clickthrough data F Radlinski, T Joachims Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007	221	2007
Mortal multi-armed bandits D Chakrabarti, R Kumar, F Radlinski, E Upfal Advances in neural information processing systems 21, 2008	214	2008
Transparent, Scrutable and Explainable User Models for Personalized Recommendation K Balog, F Radlinski, S Arakelyan The 42nd International ACM SIGIR Conference on Research and Development in …, 2019	200	2019
TREC Complex Answer Retrieval Overview. L Dietz, M Verma, F Radlinski, N Craswell TREC, 2017	161	2017
Ranked bandits in metric spaces: learning diverse rankings over large document collections A Slivkins, F Radlinski, S Gollapudi The Journal of Machine Learning Research 14 (1), 399-436, 2013	161*	2013
Redundancy, diversity and interdependent document relevance F Radlinski, PN Bennett, B Carterette, T Joachims ACM SIGIR Forum 43 (2), 46-52, 2009	161	2009
Inferring and using location metadata to personalize web search PN Bennett, F Radlinski, RW White, E Yilmaz Proceedings of the 34th international ACM SIGIR conference on Research and …, 2011	158	2011
Conversational information seeking H Zamani, JR Trippas, J Dalton, F Radlinski Foundations and Trends® in Information Retrieval 17 (3-4), 244-456, 2023	149	2023
Online evaluation for information retrieval K Hofmann, L Li, F Radlinski Foundations and Trends® in Information Retrieval 10 (1), 1-117, 2016	143	2016

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