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EMNLP
2009

Active Learning by Labeling Features

11 years 11 months ago
Active Learning by Labeling Features
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper, we propose an active learning approach in which the machine solicits "labels" on features rather than instances. In both simulated and real user experiments on two sequence labeling tasks we show that our active learning method outperforms passive learning with features as well as traditional active learning with instances. Preliminary experiments suggest that novel interfaces which intelligently solicit labels on multiple features facilitate more efficient annotation.
Gregory Druck, Burr Settles, Andrew McCallum
Added 17 Feb 2011
Updated 17 Feb 2011
Type Journal
Year 2009
Where EMNLP
Authors Gregory Druck, Burr Settles, Andrew McCallum
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