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SIGIR
2008
ACM
14 years 11 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
ESWA
2006
149views more  ESWA 2006»
14 years 11 months ago
An effective refinement strategy for KNN text classifier
Due to the exponential growth of documents on the Internet and the emergent need to organize them, the automated categorization of documents into predefined labels has received an...
Songbo Tan
PERCOM
2007
ACM
15 years 11 months ago
Structural Learning of Activities from Sparse Datasets
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Fahd Albinali, Nigel Davies, Adrian Friday
KES
2004
Springer
15 years 5 months ago
Semi-supervised Learning from Unbalanced Labeled Data - An Improvement
Abstract. We present a possibly great improvement while performing semisupervised learning tasks from training data sets when only a small fraction of the data pairs is labeled. In...
Te Ming Huang, Vojislav Kecman
CORR
2007
Springer
170views Education» more  CORR 2007»
14 years 11 months ago
The structure of verbal sequences analyzed with unsupervised learning techniques
Data mining allows the exploration of sequences of phenomena, whereas one usually tends to focus on isolated phenomena or on the relation between two phenomena. It offers invaluab...
Catherine Recanati, Nicoleta Rogovschi, Youn&egrav...