Journals / Mathematical and Computational Applications / 2011 / Cilt: 16 - Sayı: 1

Automated extraction of semantic word relations in Turkish lexicon

Pages
13–22
DOI
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⚡ TL;DR(Too Long; Didn't Read)

The results are presented by means of obtained noun-pairs and their accuracy.

📌 3 Key Takeaways

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Objective & Hypothesis:This paper studies the extraction of semantic word relations found in Turkish lexicon.
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Key Findings & Data:This study is an improvement of an earlier work [1] on semantic relations of Turkish lexicon.
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Conclusion & Impact:The results are presented by means of obtained noun-pairs and their accuracy.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

This paper studies the extraction of semantic word relations found in Turkish lexicon. Main goal of the study is to build an effective lexical-conceptual database and contribute to natural language processing (NLP) studies in Turkish. Fundamental word relations to be studied are meronymy (part-whole), synonymy, antonymy and hypernymy (hierarchical). This study is an improvement of an earlier work [1] on semantic relations of Turkish lexicon. It was inspired by well known projects such as Rose [2], ThinkMap [3], and WordNet [4]. An online dictionary provided by Turkish Language Foundation (TDK) [5] is used as the corpus in this study. The dictionary contains more than 63K lexemes. Morphological analysis are done by using a tool called Zemberek [6]. The results are presented by means of obtained noun-pairs and their accuracy.

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Cite This Article

ORHAN, Z., PEHLİVAN, İ., USLAN, V., ÖNDER, P. (2011). Automated extraction of semantic word relations in Turkish lexicon. Mathematical and Computational Applications, Cilt: 16 - Sayı: 1, 13–22. https://ajindex.com/articles/280498

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References (1)

  1. Z.Orhan and P. Önder, Türkçe için İlişkili Bilgi Tabanı ve Sözcük Ağı Geliştirilmesi, 6. Uluslararası Türk Dili Kurultayı Bildiri Kitabı, Ankara,Turkey, 2008. 2.Rose, Retrieved 08.20. 2009: http://teachrose.com/index.php 3.Thinkmap, Retrieved 08.20. 2009: http://www.visualthesaurus.com 4.WordNet, Retrieved 05.20.2009: http://wordnetweb.princeton.edu/perl/webwn 5.TDK Dictionary, Retrieved 01.10.2009: http://www.tdk.gov.tr 6.Zemberek, Retrieved 08.20.2009 http://code.google.eom/p/zemberek/ 7.M. P. Lewis (ed.),. Ethnologue: Languages of the World, Sixteenth edition. Dallas, Tex.: SIL International. Retrieved 04.12.2009: http://www.ethnologue.com/ 8.C. Bariere, From A Children's First Dictionary To A Lexical Knowledge Base of Conceptual Graphs, PhD Thesis, Simon Fraser University, Canada, 1997. 9.C. Fellbaum, WordNet: An Electronic Lexical Database, The MIT Press, 1998. 10.WordNet, Retrieved 04.12.2009:http://wordnet.princeton.edu/ 11.G. Lewis, Turkish Grammar, Oxford University Press, 1996. 12.D. Jurafsky and J.H. Martin, Speech and Language Processing, New Jersey, 2006. 13.R. Sanyal, Unsupervised Machine Learning Approach to Word Stemming, Project Guide in Indian Institute of Information Technology, Allahabad, 2006. 14.R. Kohavi and F. Provost, Special Issue on Applications of Machine Learning and the Knowledge Discovery Process, Machine Learning, Vol.30, No.2-3, 1998.