Abstract

Currently, the use of Indonesian language on the internet is growing rapidly and many of the existing sentences contain ambiguous words. In Natural Language Processing the problem to find out the meaning of an ambiguous word is called Word Sense Disambiguation. Word sense disambiguation is a problem about how we know the meaning of an ambiguous word in a given sentence. Many uses if we can solve word sense disambiguation problems such as can be used for text classification, text clustering and for machine translation. In this paper, we propose the use of SVM algorithm with TF-IDF as the feature extraction method and Wikipedia as the training data to solve the WSD problem of Indonesian language. The results of our proposed method reach an accuracy level of 0.877.

Original languageEnglish
Title of host publicationProceedings - 2018 International Seminar on Application for Technology of Information and Communication
Subtitle of host publicationCreative Technology for Human Life, iSemantic 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages239-243
Number of pages5
ISBN (Electronic)9781538674864
DOIs
Publication statusPublished - 27 Nov 2018
Event3rd International Seminar on Application for Technology of Information and Communication, iSemantic 2018 - Semarang, Indonesia
Duration: 21 Sept 201822 Sept 2018

Publication series

NameProceedings - 2018 International Seminar on Application for Technology of Information and Communication: Creative Technology for Human Life, iSemantic 2018

Conference

Conference3rd International Seminar on Application for Technology of Information and Communication, iSemantic 2018
Country/TerritoryIndonesia
CitySemarang
Period21/09/1822/09/18

Keywords

  • SVM
  • TF-IDF
  • Wikipedia
  • Word Sense Disambiguation

Fingerprint

Dive into the research topics of 'Word Sense Disambiguation in Bahasa Indonesia Using SVM'. Together they form a unique fingerprint.

Cite this