SODA

An Intrinsic Stopping Criterion for Committee-Based Active Learning

Olsson, Fredrik and Tomanek, Katrin (2009) An Intrinsic Stopping Criterion for Committee-Based Active Learning. In: Thirteenth Conference on Computational Natural Language Learning (CoNLL), 4-5 June 2009, Boulder, Colorado, USA.

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Abstract

As supervised machine learning methods are increasingly used in language technology, the need for high-quality annotated language data becomes imminent. Active learning (AL) is a means to alleviate the burden of annotation. This paper addresses the problem of knowing when to stop the AL process without having the human annotator make an explicit decision on the matter. We propose and evaluate an intrinsic criterion for committee-based AL of named entity recognizers.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:active learning, machine learning, committee-based active learning, named entity recognition
ID Code:3614
Deposited By:Fredrik Olsson
Deposited On:10 Jun 2009
Last Modified:18 Nov 2009 16:24

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