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ICDM
2003
IEEE
126views Data Mining» more  ICDM 2003»
13 years 9 months ago
Mining Relevant Text from Unlabelled Documents
Automatic classification of documents is an important area of research with many applications in the fields of document searching, forensics and others. Methods to perform class...
Daniel Barbará, Carlotta Domeniconi, Ning K...
KDD
2003
ACM
157views Data Mining» more  KDD 2003»
14 years 4 months ago
Cross-training: learning probabilistic mappings between topics
Classification is a well-established operation in text mining. Given a set of labels A and a set DA of training documents tagged with these labels, a classifier learns to assign l...
Sunita Sarawagi, Soumen Chakrabarti, Shantanu Godb...
SIGIR
2008
ACM
13 years 3 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
DASFAA
2004
IEEE
135views Database» more  DASFAA 2004»
13 years 7 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
AAAI
2004
13 years 5 months ago
Text Classification by Labeling Words
Traditionally, text classifiers are built from labeled training examples. Labeling is usually done manually by human experts (or the users), which is a labor intensive and time co...
Bing Liu, Xiaoli Li, Wee Sun Lee, Philip S. Yu