Andrew McCallum

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	전체	2016년 이후
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Michael WickUniversity of Massachusettscs.umass.edu의 이메일 확인됨
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Tom MitchellFounders University Professor of Machine Learning, Carnegie Mellon Universitycs.cmu.edu의 이메일 확인됨
Rajarshi DasPh.D. Student UMass, Amherstcs.umass.edu의 이메일 확인됨
Luke VilnisResearch Scientist, Googlecs.umass.edu의 이메일 확인됨
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Hanna WallachPartner Research Manager, Microsoft Researchdirichlet.net의 이메일 확인됨
Pat VergaResearch Scientist Googlegoogle.com의 이메일 확인됨
Dayne FreitagProgram Director, SRI Internationalai.sri.com의 이메일 확인됨
Manzil ZaheerGoogle Researchcmu.edu의 이메일 확인됨
Nicholas MonathPhD Student, University of Massachusetts Amherstcs.umass.edu의 이메일 확인됨
Gideon MannBloomberg LPbloomberg.net의 이메일 확인됨

Andrew McCallum

Distinguished Professor of Computer Science, University of Massachusetts Amherst

cs.umass.edu의 이메일 확인됨 - 홈페이지

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


제목 서지정보순 정렬 연도순 정렬 제목순 정렬	인용 인용	연도
Conditional random fields: Probabilistic models for segmenting and labeling sequence data J Lafferty, A McCallum, FCN Pereira	15974	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	5104	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	3944	2000
Mallet: A machine learning for language toolkit AK McCallum http://mallet. cs. umass. edu, 2002	2756	2002
An introduction to conditional random fields for relational learning C Sutton, A McCallum Introduction to statistical relational learning 2, 93-128, 2006	2371	2006
An introduction to conditional random fields for relational learning C Sutton, A McCallum Introduction to statistical relational learning 2, 93-128, 2006	2368	2006
Maximum entropy Markov models for information extraction and segmentation. A McCallum, D Freitag, FCN Pereira Icml 17 (2000), 591-598, 2000	1921	2000
Introduction to statistical relational learning D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ... MIT press, 2007	1815	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	1697	2006
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	1476	2011
Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons A McCallum, W Li	1468	2003
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	1437	2000
Toward optimal active learning through monte carlo estimation of error reduction N Roy, A McCallum ICML, Williamstown 2, 441-448, 2001	1376	2001
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	1292	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	1127	1998
Distributional clustering of words for text classification LD Baker, AK McCallum Proceedings of the 21st annual international ACM SIGIR conference on …, 1998	1095	1998
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	1020	2010
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	973	1998
Automating the construction of internet portals with machine learning AK McCallum, K Nigam, J Rennie, K Seymore Information Retrieval 3 (2), 127-163, 2000	937	2000
Bow: A toolkit for statistical language modeling, text retrieval, classification and clustering AK McCallum CMU: Pittsburgh, PA, 1996	937*	1996

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