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Kamal Nigam, Andrew McCallum, Sebastian Thrun, and Tom Mitchell. Learning to classify text from labeled and unlabeled documents. In Jack Mostow and Charles Rich, editors, Proceedings of the Fifteenth National Conference on Arti cial Intelligence (AAAI-98), pages 792-799, Menlo Park, CA, USA, 1998. AAAI Press /MIT Press.

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....of our unique goals in this paper is to study the combination of anomaly and misuse detection in one model to improve overall performance. We are not aware of closely related work in the generation of training data belonging to an unknown opposite class. Given unlabeled instances, Nigam et al. [13] assigned labels to them using a classifier trained from labeled data and put them in the training set for another round of training. In a skewed distribution scenario, Kubat and Matwin [7] attempted to remove majority instances too close to and too far from the decision boundary. Maxion and Tan ....

Kamal Nigam, Andrew McCallum, Sebastian Thrun, and Tom Mitchell. Learning to classify text from labeled and unlabeled documents. In Proceedings of Fifteenth National Conference on Artificial Intelligence (AAAI-98), 1998.


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....attributes inferred by the classifier in previous iterations. Other work along these lines include co learning [2] 20] and probabilistic relational models [10] Also related is the work on incorporating the clustering of the test set (unlabeled data) when building the classification model [13] [23]. Pang et al. 24] classify the overall sentiment (either positive or negative) of movie reviews using text based classification techniques. Their domain appears to have sufficient distinguishing words between the classes for text based classification to do reasonably well, though interestingly ....

K. Nigam, A. K. McCallum, S. Thrun, and T. M. Mitchell. Learning to classify text from labeled and unlabeled documents. In Proc. of AAAI-98, 15th Conference of the American Association for Artificial Intelligence, pages 792--799, Madison, US, 1998. AAAI Press, Menlo Park, US.


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Nigam, K., McCallum, A., Thrun, S., and Mitchell, T. (1998). Learning to classify text from labeled and unlabeled documents. In Proceedings of the AAAI98.


Text Clustering with Extended User Feedback - Huang, Mitchell (2006)   Self-citation (Mitchell)   (Correct)

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K. Nigam, A. K. McCallum, S. Thrun, and T. M. Mitchell. Learning to classify text from labeled and unlabeled documents. In AAAI-98, 1998.


Learning to Extract Entities from Labeled and Unlabeled Text - Jones (2005)   Self-citation (Mitchell)   (Correct)

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Nigam, K., McCallum, A., Thrun, S., & Mitchell, T. (1998). Learning to classify text from labeled and unlabeled documents. AAAI-98.


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Kamal Nigam, Andrew McCallum, Sebastian Thrun, and Tom Mitchell. Learning to Classify Text from Labeled and Unlabeled Documents. In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), pp. 792-799. 1998.


Concept Drift and the Importance of Examples - Klinkenberg, Rüping (2002)   (1 citation)  (Correct)

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Kamal Nigam, Andrew McCallum, Sebastian Thrun, and Tom Mitchell. Learning to classify text from labeled and unlabeled documents. In Jack Mostow and Charles Rich, editors, Proceedings of the Fifteenth National Conference on Arti cial Intelligence (AAAI-98), pages 792-799, Menlo Park, CA, USA, 1998. AAAI Press /MIT Press.


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K. Nigam, A.K. McCallum, S. Thrun, and T.M. Mitchell, "Learning to Classify Text from Labeled and Unlabeled Documents," Proc. Nat'l Conf. Artificial Intelligence (AAAI '98), 1998.


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Nigam, K., McCallum, A. K., Thrun, S., & Mitchell, T. M. (1998). Learning to classify text from labeled and unlabeled documents. AAAI-98, 15th Conference of the American Association for Artificial Intelligence (pp.


Asymmetric Missing-Data Problems: Overcoming the Lack of.. - Aleksander Kocz And (2002)   (Correct)

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Nigam, K., McCallum, A. K., Thrun, S. and Mitchell, T.: 2000, Learning to classify text from labeled and unlabeled documents, 39(2), 103134.


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K. Nigam, A. McCallum, S. Thrun, and T. Mitchell. Learning to classify text from labeled and unlabeled documents. AAAI, 1998.


Pruning the Vocabulary for Better Context Recognition - Madsen, Sigurdsson, Hansen, .. (2004)   (Correct)

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K. Nigam, A.K. McCallum, S. Thrun, and T.M. Mitchell. Learning to classify text from labeled and unlabeled documents. In Proceedings of AAAI-98, 15th Conference of the American Association for Artificial Intelligence, pages 792--799, Madison, US, 1998. AAAI Press, Menlo Park, US.


Clustering with Propagation for Hierarchical Document.. - Sona, al.   (Correct)

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K. Nigam, A.K. McCallum, S. Thrun, and T.M. Mitchell. Learning to classify text from labeled and unlabeled documents. In Proc. of AAAI-98, 15th Conf. of the American Association for Artificial Intelligence, pages 792--799, Madison, US, 1998.


Centro Per La Ricerca - Scientifica Tecnologica Povo   (Correct)

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K. Nigam, A.K. McCallum, S. Thrun, and T.M. Mitchell. Learning to classify text from labeled and unlabeled documents. In Proc. of AAAI-98, 15th Conf. of the American Association for Arti cial Intelligence, pages 792-799, Madison, US, 1998.


Training Object Detection Models with Weakly Labeled Data - Rosenberg, Hebert (2002)   (Correct)

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Kamal Nigam, Andrew McCallum, Sebastian Thrun and Tom Mitchell. Learning to Classify Text from Labeled and Unlabeled Documents. Fifteenth National Conference on Artificial Intelligence, pp. 792-799. 1998.


Combining Multiple Clustering Systems - Boulis, Ostendorf   (Correct)

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Nigam, K., McCallum, A., Thrun, S., Mitchell, T.: Learning to classify text from labeled and unlabeled documents. In: Proc. of AAAI. (1998) 792--799


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K. Nigam, A. K. McCallum, S. Thrun, and T. M. Mitchell. Learning to classify text from labeled and unlabeled documents. In Proceedings of AAAI-98, 15th Conference of the American Association for Arti cial Intelligence, pages 792-799, Madison, US, 1998. AAAI Press, Menlo Park, US.


Clustering Documents in a Web Directory - Adami, Paolo, Avesani, Sona (2003)   (Correct)

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K. Nigam, A. McCallum, S. Thrun, and T. Mitchell. Learning to classify text from labeled and unlabeled documents. In Proc. of AAAI-98, 15th Conf. of the American Association for Artificial Intelligence, pages 792--799, Madison, US, 1998.


Concept Drift and the Importance of Examples - Klinkenberg, Rüping (2002)   (1 citation)  (Correct)

No context found.

Kamal Nigam, Andrew McCallum, Sebastian Thrun, and Tom Mitchell. Learning to classify text from labeled and unlabeled documents. In Jack Mostow and Charles Rich, editors, Proceedings of the Fifteenth National Conference on Arti cial Intelligence (AAAI-98), pages 792-799, Menlo Park, CA, USA, 1998. AAAI Press /MIT Press.


Training Object Detection Models with Weakly Labeled Data - Rosenberg, Hebert (2002)   (Correct)

No context found.

Kamal Nigam, Andrew McCallum, Sebastian Thrun and Tom Mitchell. Learning to Classify Text from Labeled and Unlabeled Documents. Fifteenth National Conference on Artificial Intelligence, pp. 792-799. 1998.


Inférence Grammaticale Pour . . . - Chodorowski (2001)   (Correct)

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Nigam, K., McCallum, A., Thrun, S., & Mitchell, T. (1998). Learning to classify text from labeled and unlabeled documents. In Proceedings of the 15 National Conference on Arti cial Intelligence (AAAI-98) (pp. 792-799). Madison, Wisconsin, USA.


Bootstrapping for Hierarchical Document Classification - Adami, Avesani, Sona (2003)   (1 citation)  (Correct)

No context found.

K. Nigam, A. McCallum, S. Thrun, and T. Mitchell. Learning to classify text from labeled and unlabeled documents. In Proc. of AAAI-98, 15th Conf. of the American Association for Artificial Intelligence, pages 792--799, Madison, US, 1998.


Computing Gaussian Mixture Models with EM - Using Equivalence Constraints (2003)   (Correct)

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K. Nigam, A.K. McCallum, S. Thrun, and T.M. Mitchell. Learning to classify text from labeled and unlabeled documents. In Proceedings of AAAI-98, pages 792--799, Madison, US, 1998. AAAI Press, Menlo Park, US.


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Nigam K., McCallum A., et al. 1998. Learning to classify text from labeled and unlabeled documents. In Proceedings of the 15 National Conference on Artificial Intelligence (AAAI-98).


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K. Nigam, A. Mc Callum, S. Thrun, and T. Mitchell. Learning to classify text from labeled and unlabeled documents. Machine Learning, pages 1--22, 1999.

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