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» Classification as Mining and Use of Labeled Itemsets
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ICCS
2007
Springer
14 years 2 months ago
Learning Common Outcomes of Communicative Actions Represented by Labeled Graphs
We build a generic methodology based on learning and reasoning to detect specific attitudes of human agents and patterns of their interactions. Human attitudes are determined in te...
Boris Galitsky, Boris Kovalerchuk, Sergei O. Kuzne...
SDM
2004
SIAM
174views Data Mining» more  SDM 2004»
13 years 9 months ago
Classifying Documents Without Labels
Automatic classification of documents is an important area of research with many applications in the fields of document searching, forensics and others. Methods to perform classif...
Daniel Barbará, Carlotta Domeniconi, Ning K...
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 9 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...
KDD
2002
ACM
179views Data Mining» more  KDD 2002»
14 years 8 months ago
Combining clustering and co-training to enhance text classification using unlabelled data
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
Bhavani Raskutti, Herman L. Ferrá, Adam Kow...
KDD
2007
ACM
190views Data Mining» more  KDD 2007»
14 years 8 months ago
Model-shared subspace boosting for multi-label classification
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Rong Yan, Jelena Tesic, John R. Smith