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An e-Learning toolbox based on rule-based fuzzy approaches

Author
Nebot, A.; Mugica, F.; Castro, F.
Type of activity
Journal article
Journal
Applied sciences (Basel)
Date of publication
2020-09-28
Volume
10
Number
19
First page
1
Last page
21
DOI
10.3390/app10196804
Repository
http://hdl.handle.net/2117/333099 Open in new window
URL
https://www.mdpi.com/2076-3417/10/19/6804 Open in new window
Abstract
In this paper, an e-Learning toolbox based on a set of fuzzy logic data mining techniques is presented. The toolbox is mainly based on the fuzzy inductive reasoning (FIR) methodology and two of its key extensions: (i) the linguistic rules extraction algorithm (LR-FIR), which extracts comprehensible and consistent sets of rules describing students’ learning behavior, and (ii) the causal relevance approach (CR-FIR), which allows to reduce uncertainty during a student’s performance prediction s...
Citation
Nebot, A.; Múgica, F.; Castro, F. An e-Learning toolbox based on rule-based fuzzy approaches. "Applied sciences", 28 Setembre 2020, vol. 10, núm. 19, p. 1-21.
Keywords
CR-FIR, Data mining, FIR, LR-FIR, Toolbox, e-Learning
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
SOCO - Soft Computing

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