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» Joins that Generalize: Text Classification Using WHIRL
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ICML
2005
IEEE
14 years 8 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...
MLDM
2007
Springer
14 years 1 months ago
PE-PUC: A Graph Based PU-Learning Approach for Text Classification
This paper presents a novel solution for the problem of building text classifier using positive documents (P) and unlabeled documents (U). Here, the unlabeled documents are mixed w...
Shuang Yu, Chunping Li
SMC
2010
IEEE
186views Control Systems» more  SMC 2010»
13 years 5 months ago
Semantic enrichment of text representation with wikipedia for text classification
—Text classification is a widely studied topic in the area of machine learning. A number of techniques have been developed to represent and classify text documents. Most of the t...
Hiroki Yamakawa, Jing Peng, Anna Feldman
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
14 years 7 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 8 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...