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» Soft-Supervised Learning for Text Classification
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107
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KDD
2004
ACM
160views Data Mining» more  KDD 2004»
16 years 2 months ago
Boosting for Text Classification with Semantic Features
Abstract. Current text classification systems typically use term stems for representing document content. Semantic Web technologies allow the usage of features on a higher semantic...
Stephan Bloehdorn, Andreas Hotho
115
Voted
MICAI
2007
Springer
15 years 8 months ago
Taking Advantage of the Web for Text Classification with Imbalanced Classes
A problem of supervised approaches for text classification is that they commonly require high-quality training data to construct an accurate classifier. Unfortunately, in many real...
Rafael Guzmán-Cabrera, Manuel Montes-y-G&oa...
135
Voted
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 2 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
135
Voted
ICML
2005
IEEE
16 years 3 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...
125
Voted
CIKM
2010
Springer
15 years 24 days ago
Collaborative Dual-PLSA: mining distinction and commonality across multiple domains for text classification
:  Collaborative Dual-PLSA: Mining Distinction and Commonality across Multiple Domains for Text Classification Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhon...
Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yu...