A lexical knowledge acquisition model using unsupervised learning method

Doo Soon Park, Wonhee Yu, Kinam Park, Heui Seok Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a computational lexical entry acquisition model based on a representation model of the mental lexicon. The proposed model acquires lexical entries from a raw corpus by unsupervised learning like human. The model is composed of full-form and morpheme acquisition modules. We experimented the model with a Korean raw corpus of which size is about 16 million Korean full-forms. The experimental results show that the model successively acquires major Korean fullforms and morphemes with the average precision of 100% and 99.04%, respectively.

Original languageEnglish
Title of host publication2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010
DOIs
Publication statusPublished - 2010
Event5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010 - Sanya, China
Duration: 2010 Dec 162010 Dec 18

Publication series

Name2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010

Other

Other5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010
CountryChina
CitySanya
Period10/12/1610/12/18

Keywords

  • Lexical acquisition
  • Lexical entry
  • Unsupervised learning

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

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  • Cite this

    Park, D. S., Yu, W., Park, K., & Lim, H. S. (2010). A lexical knowledge acquisition model using unsupervised learning method. In 2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010 [5678174] (2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010). https://doi.org/10.1109/ICUT.2010.5678174