Genre Classification
We investigated appropriate ontologies and optimal supervised and unsupervised machine learning methods for the development of genre classifiers, specifically for resource-scarce languages.
Snyman, Van Huyssteen & Daelemans 2014
Snyman, Dirk P., Gerhard B. Van Huyssteen, and Walter Daelemans. 2014. “Outomatiese genreklassifikasie vir Afrikaans [Automatic genre classification for Afrikaans].”
Snyman, Van Huyssteen & Daelemans 2012
Snyman, Dirk, Gerhard B. Van Huyssteen, and Walter Daelemans. 2012. “Cross-lingual genre classification for closely related languages.” Proceedings of the Twenty-Third Annual Symposium of the
Snyman, Van Huyssteen & Daelemans 2011
Snyman, Dirk P., Gerhard B. Van Huyssteen, and Walter Daelemans. 2011. “Automatic genre classification for resource scarce languages.” Proceedings of the 2011 Conference of the
Keywords
2003
2005
2007
2008
2010
2011
2012
2014
2015
2017
2018
2020
2021
2022
Afrikaans
BLaRK
closely-related languages
cognitive grammar
cognitive linguistics
compound
compound splitting
construction grammar
corpus linguistics
Dutch
human language technology
human language technology audit
language audit
language resource infrastructure
language resource management
language resources
lexicography
machine learning
machine translation
morphological analysis
morphology
orthography
recycling
resource-scarce languages
semantic analysis
semantics
South Africa
spelling checker
swearing
technology audit
terminology