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Author: Guillaume Petiot

Affiliation: Catholic Institute of Toulouse, France

Keyword(s): Decision Making, Educational Information System, Possibility Theory, Possibilistic Networks, Uncertain Gates.

Related Ontology Subjects/Areas/Topics: Advanced Applications of Fuzzy Logic ; Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems

Abstract: Learning Management Systems allow us to retrieve a large scale of data about learners in order to better understand them and how they learn. Thus, it is possible to suggest educational differentiated approaches which take into account the students’ specific needs. The knowledge about the behavior of learners can be extracted by datamining or can be provided by teachers. The available data is often imprecise and incomplete. The possibility theory provides a solution to these problems. The modeling of knowledge can be performed by a possibilistic network but it requires the definition of all Conditional Possibility distributions. This constitutes a limitation for complex knowledge modeling. Uncertain Gates allow, as Noisy Gates in the probability theory, the automatic calculation of Conditional Possibility Tables. The existing Uncertain MIN and Uncertain MAX connectors are not sufficient for applications which need a compromise between both connectors. Therefore we have developed new U ncertain Compromise connectors. In this paper, we will present an experimentation of educational indicator calculation for a decision support system using Uncertain Gates. (More)

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Paper citation in several formats:
Petiot, G. (2018). The Calculation of Educational Indicators by Uncertain Gates. In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-298-1; ISSN 2184-4992, SciTePress, pages 379-386. DOI: 10.5220/0006671303790386

@conference{iceis18,
author={Guillaume Petiot.},
title={The Calculation of Educational Indicators by Uncertain Gates},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2018},
pages={379-386},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006671303790386},
isbn={978-989-758-298-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - The Calculation of Educational Indicators by Uncertain Gates
SN - 978-989-758-298-1
IS - 2184-4992
AU - Petiot, G.
PY - 2018
SP - 379
EP - 386
DO - 10.5220/0006671303790386
PB - SciTePress

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