Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/4627
Title: Verb detection in Turkish using logistic regression analysis
Authors: Kumova Metin, Senem
Kişla T.
Karaog?lan B.
Keywords: Logistic regression
POS tagging
Turkish
Fundamental group
Linguistic categories
Logistic regression analysis
Logistic regression method
Logistic regressions
Nouns and verbs
Numerical features
POS tagging
Rule based
Turkish
Turkishs
Linguistics
Regression analysis
Abstract: In this paper, we investigated the features which discriminates verbs in Turkish. Though, words in Turkish can be classified in eight different linguistic categories (noun, verb, adjective, pronoun, adverb, postposition, conjunction and interjection), they can be discriminated in two fundamental groups as nouns and verbs. We have utilized logistic regression method to determine and compare the features based on sentence and word properties considering that all linguistic categories except verbs can be merged into the to the noun originated group. The strength of both categorical (such as inclusion of capital letters, apostrophes) and numerical features (such as position in sentence) in verb discrimination are examined and results are presented. We believe that this study may contribute to the time consuming rule based or probabilistic POS tagging applications since logistic regression analysis gives an immediate foresight of verbs. © 2011 Praise Worthy Prize S.r.l.
URI: https://hdl.handle.net/20.500.14365/4627
ISSN: 1828-6003
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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