Integration of data mining techniques to postgreSQL database manager system

Data mining is a technique that allows to obtain patterns or models from the gathered data. This technique is applied in all kind of environments such as in the biological field, educational and financial applications, industry, police, and political processes. Within data mining there are several techniques, among which are the induction of rules and decision trees which, according to various studies carried out, are among the most used. This research analyzes decision tree data mining techniques and induction rules to integrate several of its algorithms into PostgreSQL database management system (DBMS). Through an experiment, it was found that when the algorithms are integrated to the manager, the response times and the results obtained are higher.

• Autores: amelec, viloria; Camargo ACUÑA, Genesis Yulie; Alcázar Franco, Daniel Jesús; Hernández-Palma, Hugo; Fuentes-Pacheco, Jorge; Pallares Rambal, Etelberto
• Tipo de recurso: Article of journal
• Fecha de publicación: 2019
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/5860
• Acceso en línea: http://hdl.handle.net/11323/5860; https://doi.org/10.1016/j.procs.2019.08.080; https://repositorio.cuc.edu.co/
• Palabra clave: Data mining; Database management system; PostgreSQL; Decision-making trees; Induction rules; Procesamiento de datos; Sistema de administración de base de datos; PostgreSQL; Árboles de toma de decisiones; Reglas de inducción
• Rights: openAccess
• License: http://creativecommons.org/publicdomain/zero/1.0/