A Machine Learning Approach to Multiword Expression Extraction
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F08%3A10077971" target="_blank" >RIV/00216208:11320/08:10077971 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
A Machine Learning Approach to Multiword Expression Extraction
Original language description
This paper describes our participation in the MWE 2008 evaluation campaign focused on ranking MWE candidates. Our ranking system employed 55 association measures combined by standard statistical-classification methods modified to provide scores for ranking. Our results were crossvalidated and compared by Mean Average Precision. In most of the experiments we observed significant performance improvement achieved by methods combining multiple association measures.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
AI - Linguistics
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the LREC 2008 Workshop Towards a Shared Task for Multiword Expressions
ISBN
2-9517408-4-0
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
ELRA
Place of publication
Marrakech, Morocco
Event location
Marrakech, Morocco
Event date
Jun 1, 2008
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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