The impact of collocational features in Turkish word sense disambiguation

Bahar Ilgen*, Eşref Adali, A. Cüneyd Tantuǧ

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

Abstract

Word Sense Disambiguation (WSD) is the task of choosing the most appropriate sense of a word having multiple senses in a given context. Collocational features acquired from the words in neighborship with the ambiguous word are one of the important knowledge sources in this area. This paper explores the effective sets of collocational features in Turkish in order to obtain better Turkish WSD systems. A lexical sample dataset of highly polysemous nouns and verbs has been prepared as the initial step of the work. Several supervised learning algorithms have been tested on this data by supplying different feature sets to select the best performing features for both nouns and verbs in Turkish. Also, we investigated the impact of several collocational features of polysemous words and evaluated the performance of several supervised machine learning algorithms.

Original languageEnglish
Title of host publicationINES 2012 - IEEE 16th International Conference on Intelligent Engineering Systems, Proceedings
Pages527-530
Number of pages4
DOIs
Publication statusPublished - 2012
EventIEEE 16th International Conference on Intelligent Engineering Systems, INES 2012 - Lisbon, Portugal
Duration: 13 Jun 201215 Jun 2012

Publication series

NameINES 2012 - IEEE 16th International Conference on Intelligent Engineering Systems, Proceedings

Conference

ConferenceIEEE 16th International Conference on Intelligent Engineering Systems, INES 2012
Country/TerritoryPortugal
CityLisbon
Period13/06/1215/06/12

Keywords

  • feature selection
  • machine learning
  • Word sense disambiguation

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