Noun and Keyword Detection of Korean in Ubiquitous Environment

Authors:
Seong-Yoon Shin;Oh-Hyung Kang;Sang-Joon Park;Jong-Chan Lee;Seong-Bae Pyo;Yang-Won Rhee
Affiliations:
Dept. of Computer Information Engineering, Kunsan Natl. Univ., Korea;Dept. of Computer Information Engineering, Kunsan Natl. Univ., Korea;Dept. of Computer Information Engineering, Kunsan Natl. Univ., Korea;Dept. of Computer Information Engineering, Kunsan Natl. Univ., Korea;Dept. of Computer Software, Induk College,;Dept. of Computer Information Engineering, Kunsan Natl. Univ., Korea
Venue:
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
Year:
2009

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Abstract

In a language, noun and keyword extraction is a key element in a ubiquitous environment. When it comes to processing Korean language information, however, there are still a lot of problems with noun and keyword extraction. This paper proposes an effective noun extraction method that considers noun emergence features. The proposed method can be effectively used in areas like information retrieval where large volumes of documents and data need to be processed in a fast manner. In this paper, a category-based keyword construction method is also presented that uses an unsupervised learning technique to ensure high volumes of queries are automatically classified. Our experimental results show that the proposed method outperformed both the supervised learning-based X2 method known to excel in keyword extraction and the DF method, in terms of classification precision.