Fuzzy Modeling Built Through a Data Mining Process

Author

Wilges, B. ; Mateus, G.P. ; Nassar, S.M. ; Bastos, R.C.

Author_Institution

Univ. Fed. de Santa Catarina (UFSC), Florianopolis, Brazil

Volume

10

Issue

2

fYear

2012

fDate

3/1/2012 12:00:00 AM

Firstpage

1622

Lastpage

1626

Abstract

This work uses fuzzy logic to identify the learning profile of students in a teaching and learning environment. The purpose of this identification is to lead the student to more appropriate use of the available resources in the environment. The fuzzy modeling has been developed from a process of data mining. The mined data set has several learning profiles of several students. The classification method called Decision Tree (DT) was applied in the mining process, and for the comparison two algorithms were used. The analysis of data from the DT allowed to validate and improve the results of fuzzy modeling. This validation process can be used in the remodeling of the characteristics of any fuzzy system, it is a way to build a more harmonious and consistent model, in this case, the student profile.

Keywords

computer aided instruction; data mining; decision trees; fuzzy logic; classification method; consistent model; data mining process; decision tree; fuzzy logic; fuzzy modeling; fuzzy system characteristics; harmonious model; learning environment; student learning profile; teaching environment; validation process; Computational modeling; Data mining; Data models; Educational institutions; Fuzzy logic; Knowledge management; Mathematical model; Decision Tree; Fuzzy Modeling; Virtual Teaching Learning Environment;

fLanguage

English

Journal_Title

Latin America Transactions, IEEE (Revista IEEE America Latina)

Publisher

ieee

ISSN

1548-0992

Type

jour

DOI

10.1109/TLA.2012.6187607

Filename

6187607