Kim Myeong Gwan , Bak Yeong Taeg

The KIPS Transactions:PartB , Vol. 10, No. 6, pp. 579-586, Oct. 2003
10.3745/KIPSTB.2003.10.6.579,   PDF Download:

Abstract

In this paper, we propose a novel approach to employ emotional features to document retrieval systems. Five emotional features, such as HAPPY, SAD, ANGRY, FEAR, and DISGUST, have been used to represent Korean document. Users are allowed to use these features for retrieving their documents. Next, retrieved documents are learned by classification methods like cohesion factor, naive Bayesian, and, k-nearest neighbor approaches. In order to combine various approaches, voting method has been used. In addition, k-means clustering has been used for our experimentation. The performance of our approach proved to be better in accuracy than other methods, and be better in short texts rather than large documents.

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