Verb Detection in Turkish Using Logistic Regression Analysis

dc.contributor.author Kumova Metin, Senem
dc.contributor.author Kişla T.
dc.contributor.author Karaog?lan B.
dc.date.accessioned 2023-06-16T18:52:13Z
dc.date.available 2023-06-16T18:52:13Z
dc.date.issued 2011
dc.description.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. en_US
dc.identifier.issn 1828-6003
dc.identifier.scopus 2-s2.0-79953167157
dc.identifier.uri https://hdl.handle.net/20.500.14365/4627
dc.language.iso en en_US
dc.relation.ispartof International Review on Computers and Software en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Logistic regression en_US
dc.subject POS tagging en_US
dc.subject Turkish en_US
dc.subject Fundamental group en_US
dc.subject Linguistic categories en_US
dc.subject Logistic regression analysis en_US
dc.subject Logistic regression method en_US
dc.subject Logistic regressions en_US
dc.subject Nouns and verbs en_US
dc.subject Numerical features en_US
dc.subject POS tagging en_US
dc.subject Rule based en_US
dc.subject Turkish en_US
dc.subject Turkishs en_US
dc.subject Linguistics en_US
dc.subject Regression analysis en_US
dc.title Verb Detection in Turkish Using Logistic Regression Analysis en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.scopusid 24471923700
gdc.author.scopusid 22334152300
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.description.departmenttemp Metin, S.K., Izmir University of Economics, Department of Computer Engineering, Turkey; Kişla, T., Ege University, Department of Computer and Instructional Technologies, Turkey; Karaog?lan, B., Ege University, International Computer Institute, Turkey en_US
gdc.description.endpage 65 en_US
gdc.description.issue 1 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 60 en_US
gdc.description.volume 6 en_US
gdc.description.wosquality N/A
gdc.index.type Scopus
gdc.scopus.citedcount 0
gdc.virtual.author Kumova Metin, Senem
relation.isAuthorOfPublication 81d6fcea-c590-42aa-8443-7459c9eab7fa
relation.isAuthorOfPublication.latestForDiscovery 81d6fcea-c590-42aa-8443-7459c9eab7fa
relation.isOrgUnitOfPublication 805c60d5-b806-4645-8214-dd40524c388f
relation.isOrgUnitOfPublication 26a7372c-1a5e-42d9-90b6-a3f7d14cad44
relation.isOrgUnitOfPublication e9e77e3e-bc94-40a7-9b24-b807b2cd0319
relation.isOrgUnitOfPublication.latestForDiscovery 805c60d5-b806-4645-8214-dd40524c388f

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
VerbDetectin-Kumova.pdf
Size:
64 KB
Format:
Adobe Portable Document Format