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» Soft-Supervised Learning for Text Classification
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ICML
2004
IEEE
14 years 8 months ago
Large margin hierarchical classification
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Ofer Dekel, Joseph Keshet, Yoram Singer
ICML
2004
IEEE
14 years 8 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
ICML
2003
IEEE
14 years 8 months ago
Linear Programming Boosting for Uneven Datasets
The paper extends the notion of linear programming boosting to handle uneven datasets. Extensive experiments with text classification problem compare the performance of a number o...
Jure Leskovec, John Shawe-Taylor
IJCAI
2003
13 years 9 months ago
Learning to Classify Texts Using Positive and Unlabeled Data
In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
Xiaoli Li, Bing Liu
IS
2008
13 years 7 months ago
Mining relational data from text: From strictly supervised to weakly supervised learning
This paper approaches the relation classification problem in information extraction framework with different machine learning strategies, from strictly supervised to weakly superv...
Zhu Zhang