Simpler unsupervised POS tagging with bilingual projections

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F13%3A10194630" target="_blank" >RIV/00216208:11320/13:10194630 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Simpler unsupervised POS tagging with bilingual projections
Original language description
We present an unsupervised approach to part-of-speech tagging based on projections of tags in a word-aligned bilingual parallel corpus. In contrast to the existing state-of-the-art approach of Das and Petrov, we have developed a substantially simpler method by automatically identifying "good" training sentences from the parallel corpus and applying self-training. In experimental results on eight languages, our method achieves state-of-the-art results.
Czech name
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Czech description
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Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics
ISBN
978-1-937284-50-3
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
634-639
Publisher name
Association for Computational Linguistics
Place of publication
Sofija, Bulgaria
Event location
Sofija, Bulgaria
Event date
Aug 4, 2013
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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