Open Science Research Excellence
%0 Journal Article
%A Hrudaya Ku. Tripathy and  B. K. Tripathy and  Pradip K. Das
%D 2007 
%J  International Journal of Computer, Electrical, Automation, Control and Information Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 11, 2007
%T An Intelligent Approach of Rough Set in Knowledge Discovery Databases
%V 11
%X Knowledge Discovery in Databases (KDD) has
evolved into an important and active area of research because of
theoretical challenges and practical applications associated with the
problem of discovering (or extracting) interesting and previously
unknown knowledge from very large real-world databases. Rough
Set Theory (RST) is a mathematical formalism for representing
uncertainty that can be considered an extension of the classical set
theory. It has been used in many different research areas, including
those related to inductive machine learning and reduction of
knowledge in knowledge-based systems. One important concept
related to RST is that of a rough relation. In this paper we presented
the current status of research on applying rough set theory to KDD,
which will be helpful for handle the characteristics of real-world
databases. The main aim is to show how rough set and rough set
analysis can be effectively used to extract knowledge from large
%P 3450 - 3453