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Michael Bendersky
Michael Bendersky
Google Research
google.com üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
Discovering key concepts in verbose queries
M Bendersky, WB Croft
Proceedings of the 31st annual international ACM SIGIR conference on …, 2008
3272008
Learning concept importance using a weighted dependence model
M Bendersky, D Metzler, WB Croft
Proceedings of the third ACM international conference on Web search and data …, 2010
2172010
Learning to rank with selection bias in personal search
X Wang, M Bendersky, D Metzler, M Najork
Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016
1922016
Position bias estimation for unbiased learning to rank in personal search
X Wang, N Golbandi, M Bendersky, D Metzler, M Najork
Proceedings of the Eleventh ACM International Conference on Web Search and …, 2018
1772018
Quality-biased ranking of web documents
M Bendersky, WB Croft, Y Diao
Proceedings of the fourth ACM international conference on Web search and …, 2011
1432011
Analysis of long queries in a large scale search log
M Bendersky, WB Croft
Proceedings of the 2009 workshop on Web Search Click Data, 8-14, 2009
1352009
Parameterized concept weighting in verbose queries
M Bendersky, D Metzler, WB Croft
Proceedings of the 34th international ACM SIGIR conference on Research and …, 2011
1292011
Effective query formulation with multiple information sources
M Bendersky, D Metzler, WB Croft
Proceedings of the fifth ACM international conference on Web search and data …, 2012
1192012
Finding text reuse on the web
M Bendersky, WB Croft
Proceedings of the Second ACM International Conference on Web Search and …, 2009
1062009
Tf-ranking: Scalable tensorflow library for learning-to-rank
RK Pasumarthi, S Bruch, X Wang, C Li, M Bendersky, M Najork, J Pfeifer, ...
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
1002019
Information retrieval with verbose queries
M Gupta, M Bendersky
Foundations and Trends® in Information Retrieval 9 (3-4), 209-354, 2015
912015
Modeling higher-order term dependencies in information retrieval using query hypergraphs
M Bendersky, WB Croft
Proceedings of the 35th international ACM SIGIR conference on Research and …, 2012
872012
The lambdaloss framework for ranking metric optimization
X Wang, C Li, N Golbandi, M Bendersky, M Najork
Proceedings of the 27th ACM international conference on information and …, 2018
842018
Learning-to-Rank with BERT in TF-Ranking
S Han, X Wang, M Bendersky, M Najork
arXiv preprint arXiv:2004.08476, 2020
642020
Situational context for ranking in personal search
H Zamani, M Bendersky, X Wang, M Zhang
Proceedings of the 26th International Conference on World Wide Web, 1531-1540, 2017
642017
Semantic text matching for long-form documents
JY Jiang, M Zhang, C Li, M Bendersky, N Golbandi, M Najork
The world wide web conference, 795-806, 2019
622019
Learning groupwise multivariate scoring functions using deep neural networks
Q Ai, X Wang, S Bruch, N Golbandi, M Bendersky, M Najork
Proceedings of the 2019 ACM SIGIR international conference on theory of …, 2019
602019
Two-stage learning to rank for information retrieval
V Dang, M Bendersky, WB Croft
European Conference on Information Retrieval, 423-434, 2013
572013
Utilizing passage-based language models for document retrieval
M Bendersky, O Kurland
European Conference on Information Retrieval, 162-174, 2008
552008
Two-stage query segmentation for information retrieval
M Bendersky, WB Croft, DA Smith
Proceedings of the 32nd international acm sigir conference on research and …, 2009
542009
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