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2007

Domain Adaptation with Active Learning for Word Sense Disambiguation

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Domain Adaptation with Active Learning for Word Sense Disambiguation
When a word sense disambiguation (WSD) system is trained on one domain but applied to a different domain, a drop in accuracy is frequently observed. This highlights the importance of domain adaptation for word sense disambiguation. In this paper, we first show that an active learning approach can be successfully used to perform domain adaptation of WSD systems. Then, by using the predominant sense predicted by expectation-maximization (EM) and adopting a count-merging technique, we improve the effectiveness of the original adaptation process achieved by the basic active learning approach.
Yee Seng Chan, Hwee Tou Ng
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ACL
Authors Yee Seng Chan, Hwee Tou Ng
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