2009 SemiSupervisedActiveLearningfor

(Tomanek & Hahn, 2009) ⇒ Katrin Tomanek, and Udo Hahn. (2009). “Semi-supervised Active Learning for Sequence Labeling.” In: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP (ACL 2009).

Subject Headings: Semi-Supervised Active Learning, Linguistic Sequence Labeling.

Notes

Cited By

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Abstract

While Active Learning (AL) has already been shown to markedly reduce the annotation efforts for many sequence labeling tasks compared to random selection, AL remains unconcerned about the internal structure of the selected sequences (typically, sentences). We propose a semi-supervised AL approach for sequence labeling where only highly uncertain subsequences are presented to human annotators, while all others in the selected sequences are automatically labeled. For the task of entity recognition, our experiments reveal that this approach reduces annotation efforts in terms of manually labeled tokens by up to 60% compared to the standard, fully supervised AL scheme.

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2009 SemiSupervisedActiveLearningfor	Katrin Tomanek Udo Hahn			Semi-supervised Active Learning for Sequence Labeling						2009