A system that performs text categorization aims to assign appropriate categories from a predefined classification scheme to incoming documents. These assignments might be used for varied purposes such as filtering, or retrieval. This paper introduces a new effective model for text categorization with great corpus (more or less 1 million documents). Text categorization is performed using the Kul...

This paper proposes a model averaging method based on Kullback-Leibler distance under a homoscedastic normal error term. The resulting model average estimator is proved to be asymptotically optimal. When combining least squares estimators, the model average estimator is shown to have the same large sample properties as the Mallows model average (MMA) estimator developed by Hansen (2007). We sho...

In our series of studies on quantifying chirality, a new chirality measure is proposed in this work based on the Kullback-Leibler information entropy. The index computes the extra information that the shape function of one enantiomer carries over a normalized shape function of the racemate, while in our previous studies the shape functions of the R and S enantiomers were used considering one as...

An estimator of the Kullback-Leibler information number by using its representation as a functional of the grade density is introduced. Its strong consistency is proved under the mild conditions on the grade density. The same approach is used to study the entropy measure of bivariate dependence (mutual information). Some applications to detection theory are also given.

This paper considers the search problem, introduced by Srivastava cite{Sr}. This is a model discrimination problem. In the context of search linear models, discrimination ability of search designs has been studied by several researchers. Some criteria have been developed to measure this capability, however, they are restricted in a sense of being able to work for searching only one possibl...