Andrew McCallum

Cited by

	All	Since 2016
Citations	81633	30479
h-index	110	77
i10-index	267	204

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Co-authors

Kamal NigamGoogleVerified email at kamalnigam.com
Charles SuttonGoogle, University of EdinburghVerified email at inf.ed.ac.uk
Fernando PereiraVP and Engineering Fellow, GoogleVerified email at google.com
David MimnoAssociate Professor, Cornell UniversityVerified email at cornell.edu
Aron CulottaAssociate Professor of Computer Science, Tulane UniversityVerified email at tulane.edu
Sebastian RiedelProfessor @ University College London, Researcher @ Facebook AI ResearchVerified email at cs.ucl.ac.uk
Xuerui WangGoogle Inc.Verified email at google.com
Michael WickUniversity of MassachusettsVerified email at cs.umass.edu
Tom MitchellFounders University Professor of Machine Learning, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Sameer SinghUniversity of California, IrvineVerified email at uci.edu
Emma StrubellAssistant Professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Hanna WallachSenior Principal Researcher, Microsoft ResearchVerified email at dirichlet.net
Dayne FreitagProgram Director, SRI InternationalVerified email at ai.sri.com
Luke VilnisGraduate Research Assistant, University of Massachusetts AmherstVerified email at cs.umass.edu
David BelangerResearch Scientist, Google BrainVerified email at google.com
Rajarshi DasPh.D. Student UMass, AmherstVerified email at cs.umass.edu
Pat VergaResearch Scientist GoogleVerified email at google.com
Gideon MannBloomberg LPVerified email at bloomberg.net
Gregory DruckGraphiteVerified email at graphitehq.com
Jason RennieSoftware Engieer, GoogleVerified email at google.com

Andrew McCallum

Distinguished Professor of Computer Science, University of Massachusetts Amherst

Verified email at cs.umass.edu - Homepage

Machine Learning Natural Language Processing Information Extraction Artificial Intelligence Social Network Analysis


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Conditional random fields: Probabilistic models for segmenting and labeling sequence data J Lafferty, A McCallum, FCN Pereira	15188	2001
A comparison of event models for naive bayes text classification A McCallum, K Nigam AAAI-98 workshop on learning for text categorization 752 (1), 41-48, 1998	4845	1998
Text classification from labeled and unlabeled documents using EM K Nigam, AK McCallum, S Thrun, T Mitchell Machine learning 39 (2), 103-134, 2000	3785	2000
Mallet: A machine learning for language toolkit AK McCallum http://mallet. cs. umass. edu, 2002	2626	2002
An introduction to conditional random fields for relational learning C Sutton, A McCallum Introduction to statistical relational learning 2, 93-128, 2006	2248	2006
An introduction to conditional random fields for relational learning C Sutton, A McCallum Introduction to statistical relational learning 2, 93-128, 2006	2245	2006
Maximum entropy Markov models for information extraction and segmentation. A McCallum, D Freitag, FCN Pereira Icml 17 (2000), 591-598, 2000	1856	2000
Introduction to statistical relational learning D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ... MIT press, 2007	1731	2007
Topics over time: a non-markov continuous-time model of topical trends X Wang, A McCallum Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006	1613	2006
Efficient clustering of high-dimensional data sets with application to reference matching A McCallum, K Nigam, LH Ungar Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000	1386	2000
Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons A McCallum, W Li	1384	2003
Toward optimal active learning through monte carlo estimation of error reduction N Roy, A McCallum ICML, Williamstown, 441-448, 2001	1297	2001
Optimizing semantic coherence in topic models D Mimno, H Wallach, E Talley, M Leenders, A McCallum Proceedings of the 2011 conference on empirical methods in natural language …, 2011	1261	2011
Using maximum entropy for text classification K Nigam, J Lafferty, A McCallum IJCAI-99 workshop on machine learning for information filtering 1 (1), 61-67, 1999	1238	1999
Employing EM and pool-based active learning for text classification AK McCallumzy, K Nigamy Proc. International Conference on Machine Learning (ICML), 359-367, 1998	1083	1998
Distributional clustering of words for text classification LD Baker, AK McCallum Proceedings of the 21st annual international ACM SIGIR conference on …, 1998	1070	1998
Learning to extract symbolic knowledge from the World Wide Web M Craven, A McCallum, D PiPasquo, T Mitchell, D Freitag Carnegie-mellon univ pittsburgh pa school of computer Science, 1998	938	1998
Bow: A toolkit for statistical language modeling, text retrieval, classification and clustering AK McCallum CMU: Pittsburgh, PA, 1996	916*	1996
Modeling relations and their mentions without labeled text S Riedel, L Yao, A McCallum Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010	873	2010
Automating the construction of internet portals with machine learning AK McCallum, K Nigam, J Rennie, K Seymore Information Retrieval 3 (2), 127-163, 2000	830	2000

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