Fuzzy Modeling Built Through a Data Mining Process
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 dat...
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| Veröffentlicht in: | Revista IEEE América Latina 2012-03, Vol.10 (2), p.1622-1626 |
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| container_title | Revista IEEE América Latina |
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| creator | Wilges, B. Mateus, G. P. Nassar, S. M. Bastos, R. C. |
| description | 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. |
| doi_str_mv | 10.1109/TLA.2012.6187607 |
| format | Article |
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| subjects | Computational modeling Construction Data mining Data models Decision Tree Decision trees Educational institutions Fuzzy Fuzzy logic Fuzzy Modeling Fuzzy set theory Knowledge management Learning Mathematical model Students Studies Virtual Teaching Learning Environment |
| title | Fuzzy Modeling Built Through a Data Mining Process |
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