Using RSDM to mine socio-economic indicators

Author

Fernandez-Baizán, María Covadonga ; Ruiz, Ernestina Menasalvas ; Sánchez, José Maria Peña ; Milian, S.

Author_Institution

Dept. de Lenguajes y Sistemas Inf., Campus de Montegancedo, Madrid, Spain

Volume

2

fYear

1997

fDate

12-15 Oct 1997

Firstpage

1385

Abstract

The main objective of this paper is to briefly show the improved version of RSDM (rough set data miner) and how it works when applying it to several socio-economic indicators from different countries. RSDM is a system that is being developed by our research group at the Department of Languages and Systems at Politechnical University of Madrid to mine relational databases (RDBMs). The system runs on SUN-Solaris against data that can be managed by ORACLE or any other RDBMs. Different algorithms have been implemented making use of several data mining techniques: to reduce the number of attributes being taken into account; to calculate discriminant and characteristic rules; and to extract dependencies among attributes. The performance as well as the validity of these algorithms are shown using data from World Report ´96 (published by the World Bank)

Keywords

humanities; query processing; relational databases; social sciences computing; Politechnical University of Madrid; World Report 96; characteristic rules; data mining; dependency extraction; discriminant rules; relational databases; rough set data miner; socio-economic indicators; Agriculture; Data mining; Fossil fuels; Set theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1062-922X

Print_ISBN

0-7803-4053-1

Type

conf

DOI

10.1109/ICSMC.1997.638167

Filename

638167