A lexical knowledge acquisition model using unsupervised learning method

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

doi:10.1109/ICUT.2010.5678174

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 proceeding › Conference 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 language	English
Title of host publication	2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010
DOIs	https://doi.org/10.1109/ICUT.2010.5678174
Publication status	Published - 2010
Event	5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010 - Sanya, China Duration: 2010 Dec 16 → 2010 Dec 18

Publication series

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

Other

Other	5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010
Country/Territory	China
City	Sanya
Period	10/12/16 → 10/12/18

Keywords

Lexical acquisition
Lexical entry
Unsupervised learning

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Information Systems

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10.1109/ICUT.2010.5678174

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 Article 5678174 (2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010). https://doi.org/10.1109/ICUT.2010.5678174

A lexical knowledge acquisition model using unsupervised learning method. / Park, Doo Soon; Yu, Wonhee; Park, Kinam et al.
2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010. 2010. 5678174 (2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Park, DS, Yu, W, Park, K & Lim, HS 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, 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010, Sanya, China, 10/12/16. https://doi.org/10.1109/ICUT.2010.5678174

Park DS, Yu W, Park K, Lim HS. 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. 2010. 5678174. (2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010). doi: 10.1109/ICUT.2010.5678174

Park, Doo Soon ; Yu, Wonhee ; Park, Kinam et al. / A lexical knowledge acquisition model using unsupervised learning method. 2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010. 2010. (2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2010).

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AB - 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.

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A lexical knowledge acquisition model using unsupervised learning method

Abstract

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Keywords

ASJC Scopus subject areas

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