A statistical tagger for morphological tagging of Russian language texts

We consider a method of constructing a statistical tagger for automated morphological tagging for Russian language texts. In this method, each word is assigned with a tag that contains information about the part of speech and a full set of the word’s morphological characteristics. We employ the set...

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Bibliographic Details
Published in:Automation and remote control 2013-10, Vol.74 (10), p.1724-1732
Main Authors: Petrochenkov, V. V., Kazennikov, A. O.
Format: Article
Language:English
Subjects:
Automated
CAE) and Design
Calculus of Variations and Optimal Control
Optimization
Computer-Aided Engineering (CAD
Control
Mathematics
Mathematics and Statistics
Mechanical Engineering
Mechatronics
Robotics
Systems Theory
Topical Issue
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Summary:We consider a method of constructing a statistical tagger for automated morphological tagging for Russian language texts. In this method, each word is assigned with a tag that contains information about the part of speech and a full set of the word’s morphological characteristics. We employ the set of morphological characteristics used in the SynTagRus corpus whose material has been used to train the tagger. The tagger is based on the SVM (Support Vector Machine) approach. The developed tagger has proven to be efficient and has shown high tagging quality.
ISSN:0005-1179
1608-3032
DOI:10.1134/S0005117913100123