[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.3745/JIPS.2007.3.1.033

Feature Extraction of Concepts by Independent Component Analysis

Chagnaa, Altangerel (School of Computer Engineering and Information Technology, University of Ulsan)
Ock, Cheol-Young (School of Computer Engineering and Information Technology, University of Ulsan)
Lee, Chang-Beom (Investigation & Analysis Team, Korean Transportation Safety Agency)
Jaimai, Purev (School of Information Technology, National University of Mongolia)

Publication Information

Journal of Information Processing Systems / v.3, no.1, 2007 , pp. 33-37 More about this Journal

Abstract

Semantic clustering is important to various fields in the modem information society. In this work we applied the Independent Component Analysis method to the extraction of the features of latent concepts. We used verb and object noun information and formulated a concept as a linear combination of verbs. The proposed method is shown to be suitable for our framework and it performs better than a hierarchical clustering in latent semantic space for finding out invisible information from the data.

Keywords

Independent Component Analysis; Clustering; Latent Concepts;

Citations & Related Records

Reference

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