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» Text classification from positive and unlabeled documents
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ICML
2005
IEEE
14 years 9 months ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...
AAAI
2006
13 years 10 months ago
Comparative Experiments on Sentiment Classification for Online Product Reviews
Evaluating text fragments for positive and negative subjective expressions and their strength can be important in applications such as single- or multi- document summarization, do...
Hang Cui, Vibhu O. Mittal, Mayur Datar
AWIC
2007
Springer
14 years 2 months ago
Improving Text Classification by Web Corpora
A major difficulty of supervised approaches for text classification is that they require a great number of training instances in order to construct an accurate classifier. This pap...
Rafael Guzmán-Cabrera, Manuel Montes-y-G&oa...
KDD
2003
ACM
157views Data Mining» more  KDD 2003»
14 years 9 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...
IJCAI
2003
13 years 10 months ago
SVMC: Single-Class Classification With Support Vector Machines
Single-Class Classification (SCC) seeks to distinguish one class of data from the universal set of multiple classes. We present a new SCC algorithm that efficiently computes an ac...
Hwanjo Yu