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» Learning to Classify Texts Using Positive and Unlabeled Data
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DATAMINE
2010
122views more  DATAMINE 2010»
13 years 7 months ago
Three naive Bayes approaches for discrimination-free classification
In this paper, we investigate how to modify the Naive Bayes classifier in order to perform classification that is restricted to be independent with respect to a given sensitive att...
Toon Calders, Sicco Verwer
KDD
2008
ACM
195views Data Mining» more  KDD 2008»
14 years 7 months ago
Learning from multi-topic web documents for contextual advertisement
Contextual advertising on web pages has become very popular recently and it poses its own set of unique text mining challenges. Often advertisers wish to either target (or avoid) ...
Yi Zhang, Arun C. Surendran, John C. Platt, Mukund...
ICML
2000
IEEE
14 years 8 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
ICDM
2010
IEEE
205views Data Mining» more  ICDM 2010»
13 years 5 months ago
Knowledge File System -- A Principled Approach to Personal Information Management
The Knowledge File System (KFS) is a smart virtual file system that sits between the operating system and the file system. Its primary functionality is to automatically organize fi...
Kuiyu Chang, I. Wayan Tresna Perdana, Bramandia Ra...
ESWA
2008
140views more  ESWA 2008»
13 years 7 months ago
Web taxonomy integration with hierarchical shrinkage algorithm and fine-grained relations
We address the problem of integrating web taxonomies from different real Internet applications. Integrating web taxonomies is to transfer instances from a source to target taxonom...
Chia-Wei Wu, Richard Tzong-Han Tsai, Cheng-Wei Lee...