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Computer Systems Science and Engineering
Article
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DBLP
Article . 2019
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A Two-Level Morphological Description of Bashkir Turkish

Authors: Eyüpoğlu, Can;

A Two-Level Morphological Description of Bashkir Turkish

Abstract

In recent years, the topic of Natural Language Processing (NLP) has attracted increasing interest. Many NIP applications including machine translation, machine learning, speech recognition, sentiment analysis, semantic search and natural language generation have been developed for most of the existing languages. Besides, two-level morphological description of the language to be used is required for these applications. However, there is no comprehensive study of Bashkir Turkish in the literature. In this paper, a two-level description of Bashkir Turkish morphology is described. The description based on a root word lexicon of Bashkir Turkish is implemented using Extensible Markup Language (XML) and appended to Nuve framework. The phonetic rules of Bashkir Turkish are encoded using 41 two-level rules. This two-level morphological description is promising to be used in Bashkir Turkish oriented NLP applications. © 2019 CRL Publishing Ltd.

Country
Turkey
Related Organizations
Keywords

Natural language processing, Bashkir Turkish, Two-level morphology, Extensible markup language

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
hybrid