Active learning has been successfully applied to many natural language processing tasks for obtaining annotated data in a cost-effective manner. We propose several extensions to an active learner that adopts the margin-based uncertainty sampling framework. Experimental results on a cause detection problem involving the classification of aviation safety reports demonstrate the effectiveness of our extensions. 1.
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Persing et al. (2010) studied this question.
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