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» A parallel learning algorithm for text classification
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CIKM
2008
Springer
14 years 11 months ago
Semi-supervised text categorization by active search
In automated text categorization, given a small number of labeled documents, it is very challenging, if not impossible, to build a reliable classifier that is able to achieve high...
Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu...
ICML
2004
IEEE
15 years 10 months 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
IFIP12
2008
14 years 11 months ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
Frederic T. Stahl, Max A. Bramer, Mo Adda
COLING
1992
14 years 10 months ago
Learning Translation Templates From Bilingual Text
This paper proposes a two-phase example-based machine translation methodology which develops translation templates from examples and then translates using template matching. This ...
Hiroyuki Kaji, Yuuko Kida, Yasutsugu Morimoto
ICML
2002
IEEE
15 years 10 months ago
Active + Semi-supervised Learning = Robust Multi-View Learning
In a multi-view problem, the features of the domain can be partitioned into disjoint subsets (views) that are sufficient to learn the target concept. Semi-supervised, multi-view a...
Ion Muslea, Steven Minton, Craig A. Knoblock