Title :
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
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;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.638167
