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Turkish PoS Tagging by Reducing Sparsity with Morpheme Tags in Small Datasets
[article]
2017
arXiv
pre-print
Sparsity is one of the major problems in natural language processing. The problem becomes even more severe in agglutinating languages that are highly prone to be inflected. We deal with sparsity in Turkish by adopting morphological features for part-of-speech tagging. We learn inflectional and derivational morpheme tags in Turkish by using conditional random fields (CRF) and we employ the morpheme tags in part-of-speech (PoS) tagging by using hidden Markov models (HMMs) to mitigate sparsity.
arXiv:1703.03200v2
fatcat:4oejtwfj7jbnff2y4f2lanwsja