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» A parallel learning algorithm for text classification
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CIKM
2008
Springer
15 years 4 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
16 years 3 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
15 years 3 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
15 years 3 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
16 years 3 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