DATA MINING ON INFORMATION SYSTEM USING FUZZY ROUGH SET THEORY

Phùng Thị Thu Hiền

doi:10.34238/tnu-jst.2020.02.2330

DATA MINING ON INFORMATION SYSTEM USING FUZZY ROUGH SET THEORY

About this article

Received: 14/11/19 Revised: 26/12/19 Published: 14/02/20

Authors

Phung Thi Thu Hien , University of Economic and Technical Industries, Hanoi

Abstract

Today, thanks to the strong development of applications of information technology and Internet in many fields, a huge of database has been created. The number of records and the size of each record collected very quickly make it difficult to store and process information. Exploiting information sources from large databases effectively is an urgent issue and plays an important role in solving practical problems. In addition to traditional exploiting information methods, researchers have developed attribute reduction methods to reduce the size of the data space and eliminate irrelevant attributes. Our attribute reduction is based on the dependence between attributes in traditional rough set theory and in fuzzy rough set. The author built the tool which is inclusion degree and tolerance-based contingency table to solve the problem of finding the approximation set on set-valued information systems.

Keywords

rough set; fuzzy rough set; set-valued information system; contingency table; reduct.

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DOI: https://doi.org/10.34238/tnu-jst.2020.02.2330

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