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» Semi-supervised Text Classification Using Partitioned EM
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DASFAA
2004
IEEE
135views Database» more  DASFAA 2004»
15 years 3 months ago
Semi-supervised Text Classification Using Partitioned EM
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
Gao Cong, Wee Sun Lee, Haoran Wu, Bing Liu
ICML
2004
IEEE
16 years 12 days ago
Co-EM support vector learning
Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms ...
Ulf Brefeld, Tobias Scheffer
ML
2000
ACM
124views Machine Learning» more  ML 2000»
14 years 11 months ago
Text Classification from Labeled and Unlabeled Documents using EM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
ICML
1998
IEEE
16 years 12 days ago
Employing EM and Pool-Based Active Learning for Text Classification
This paper shows how a text classifier's need for labeled training documents can be reduced by taking advantage of a large pool of unlabeled documents. We modify the Query-by...
Andrew McCallum, Kamal Nigam
ICDAR
2009
IEEE
15 years 6 months ago
Enhanced Text Extraction from Arabic Degraded Document Images Using EM Algorithm
This paper presents a new enhanced text extraction algorithm from degraded document images on the basis of the probabilistic models. The observed document image is considered as a...
Wafa Boussellaa, Aymen Bougacha, Abderrazak Zahour...