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Ensemble of Classifiers for Noise Detection in PoS Tagged Corpora
2000 (English)In: Proceedings of the Third International Workshop on TEXT, SPEECH and DIALOGUE, 2000, 27-32 p.Conference paper (Refereed)
Abstract [en]

In this paper we apply the ensemble approach to the identification of incorrectly annotated items (noise) in a training set. In a controlled experiment, memory-based, decision tree-based and transformation-based classifiers are used as a filter to detect and remove noise deliberately introduced into a manually tagged corpus. The results indicate that the method can be successfully applied to automatically detect errors in a corpus.

Place, publisher, year, edition, pages
2000. 27-32 p.
National Category
Language Technology (Computational Linguistics)
Research subject
Computational Linguistics
URN: urn:nbn:se:uu:diva-19665OAI: oai:DiVA.org:uu-19665DiVA: diva2:47437
Available from: 2006-11-30 Created: 2006-11-30 Last updated: 2016-03-08

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Megyesi, Beata
Language Technology (Computational Linguistics)

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