DocumentCode :
3637221
Title :
Tagger voting improves morphosyntactic tagging accuracy on Croatian texts
Author :
Željko Agić;Marko Tadić
Author_Institution :
Department of Information Sciences, Faculty of Humanities and Social Sciences, University of Zagreb, Ivana Luč
fYear :
2010
Firstpage :
61
Lastpage :
66
Abstract :
We present results of an experiment dealing with combining outputs of five part-of-speech taggers via tagger voting in order to improve the overall accuracy of morphosyntactic tagging of Croatian texts using a subset of the Multext-East v3 tagset. The increase in accuracy over the best-performing single tagger is shown to exist, but not to be statistically significant. We discuss the performance of the five single taggers, the overlaps between tagger pairs, the reduced tagset and the voting scheme, along with scores for five meaningful tagger combinations in the voting scheme and future work plans.
Keywords :
"Tagging","Accuracy","Hidden Markov models","Support vector machines","Training","Assembly","Stochastic processes"
Publisher :
ieee
Conference_Titel :
Information Technology Interfaces (ITI), 2010 32nd International Conference on
ISSN :
1330-1012
Print_ISBN :
978-1-4244-5732-8
Type :
conf
Filename :
5546366
Link To Document :
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