Kamal Nigam
Kamal Nigam
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Verified email at kamalnigam.com
Title
Cited by
Cited by
Year
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
50071998
Text classification from labeled and unlabeled documents using EM
K Nigam, AK McCallum, S Thrun, T Mitchell
Machine learning 39 (2), 103-134, 2000
39002000
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
14232000
Analyzing the effectiveness and applicability of co-training
K Nigam, R Ghani
Proceedings of the ninth international conference on Information and …, 2000
12952000
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
12701999
Employing EM and pool-based active learning for text classification
AK McCallumzy, K Nigamy
Proc. International Conference on Machine Learning (ICML), 359-367, 1998
11171998
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
9631998
Automating the construction of internet portals with machine learning
AK McCallum, K Nigam, J Rennie, K Seymore
Information Retrieval 3 (2), 127-163, 2000
8972000
Learning to construct knowledge bases from the World Wide Web
M Craven, D DiPasquo, D Freitag, A McCallum, T Mitchell, K Nigam, ...
Artificial intelligence 118 (1-2), 69-113, 2000
6552000
Using EM to classify text from labeled and unlabeled documents
K Nigam, A McCallum, S Thrun, T Mitchell
CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE, 1998
5441998
Using EM to classify text from labeled and unlabeled documents
K Nigam, A McCallum, S Thrun, T Mitchell
CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE, 1998
5421998
Using EM to classify text from labeled and unlabeled documents
K Nigam, A McCallum, S Thrun, T Mitchell
CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE, 1998
5421998
A machine learning approach to building domain-specific search engines
A McCallum, K Nigam, J Rennie, K Seymore
IJCAI 99, 662-667, 1999
2731999
Deriving marketing intelligence from online discussion
N Glance, M Hurst, K Nigam, M Siegler, R Stockton, T Tomokiyo
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005
2562005
Building domain-specific search engines with machine learning techniques
A McCallumzy, K Nigamy, J Renniey, K Seymorey
Proceedings of the AAAI Spring Symposium on Intelligent Agents in Cyberspace …, 1999
2501999
Topical sentiments in electronically stored communications
KP Nigam, MF Hurst
US Patent 7,523,085, 2009
2462009
Topical sentiments in electronically stored communications
KP Nigam, MF Hurst
US Patent 7,523,085, 2009
2462009
Intrusive software management
N Provos, Y Zhou, CW Bavor, EL Davis, M Palatucci, KP Nigam, ...
US Patent App. 12/041,309, 2009
2452009
Using unlabeled data to improve text classification
KP Nigam
Carnegie Mellon University, 2001
2302001
Semi-Supervised Text Classification Using EM.
K Nigam, A McCallum, TM Mitchell
Semi-Supervised Learning, 32-55, 2006
1892006
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Articles 1–20