Feature Extraction of Concepts by Independent Component Analysis

Semantic clustering is important to various fields in the modern 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.