POS Tagging in Amazighe Using Support Vector Machines and Conditional Random Fields
Identifieur interne : 000426 ( Main/Exploration ); précédent : 000425; suivant : 000427POS Tagging in Amazighe Using Support Vector Machines and Conditional Random Fields
Auteurs : Mohamed Outahajala [Maroc] ; Yassine Benajiba [États-Unis] ; Paolo Rosso [Espagne] ; Lahbib Zenkouar [Maroc]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2011.
Abstract
Abstract: The aim of this paper is to present the first Amazighe POS tagger. Very few linguistic resources have been developed so far for Amazighe and we believe that the development of a POS tagger tool is the first step needed for automatic text processing. The used data have been manually collected and annotated. We have used state-of-art supervised machine learning approaches to build our POS-tagging models. The obtained accuracy achieved 92.58% and we have used the 10-fold technique to further validate our results.
Url:
DOI: 10.1007/978-3-642-22327-3_28
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">Abstract: The aim of this paper is to present the first Amazighe POS tagger. Very few linguistic resources have been developed so far for Amazighe and we believe that the development of a POS tagger tool is the first step needed for automatic text processing. The used data have been manually collected and annotated. We have used state-of-art supervised machine learning approaches to build our POS-tagging models. The obtained accuracy achieved 92.58% and we have used the 10-fold technique to further validate our results.</div>
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