PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Bringing Active Learning to Life
Ines Rehbein, Josef Ruppenhofer and Alexis Palmer
In: The 23rd International Conference on Computational Linguistics (COLING 2010), 23-27 Aug 2010, Beijing, China.

Abstract

Active learning has been applied to different NLP tasks, with the aim of limiting the amount of time and cost for human annotation. Most studies on active learning have only simulated the annotation scenario, using relabelled gold standard data. We present the first active learning experiment for Word Sense Disambiguation with human annotators in a realistic environment, using fine-grained sense distinctions, and investigate whether AL can reduce annotation cost and boost classifier performance when applied to a real-world task.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:7990
Deposited By:Ines Rehbein
Deposited On:17 March 2011