APPROXIMATE REASONING BASED ON LINGUISTIC MODIFIERS IN A LEARNING SYSTEM

Saoussen Bel Hadj Kacem, Amel Borgi, Moncef Tagina

Abstract

Approximate reasoning, initially introduced in fuzzy logic context, allows reasoning with imperfect knowledge. We have proposed in a previous work an approximate reasoning based on linguistic modifiers in a symbolic context. To apply such reasoning, a base of rules is needed. We propose in this paper to use a supervised learning system named SUCRAGE, that automatically generates multi-valued classification rules. Our reasoning is used with this rule base to classify new objects. Experimental tests and comparative study with two initial reasoning modes of SUCRAGE are presented. This application of approximate reasoning based on linguistic modifiers gives satisfactory results. Besides, it provides a comfortable linguistic interpretation to the human mind thanks to the use of linguistic modifiers.

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Paper Citation


in Harvard Style

Bel Hadj Kacem S., Borgi A. and Tagina M. (2010). APPROXIMATE REASONING BASED ON LINGUISTIC MODIFIERS IN A LEARNING SYSTEM . In Proceedings of the 5th International Conference on Software and Data Technologies - Volume 2: ICSOFT, ISBN 978-989-8425-23-2, pages 431-437. DOI: 10.5220/0002924204310437


in Bibtex Style

@conference{icsoft10,
author={Saoussen Bel Hadj Kacem and Amel Borgi and Moncef Tagina},
title={APPROXIMATE REASONING BASED ON LINGUISTIC MODIFIERS IN A LEARNING SYSTEM},
booktitle={Proceedings of the 5th International Conference on Software and Data Technologies - Volume 2: ICSOFT,},
year={2010},
pages={431-437},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002924204310437},
isbn={978-989-8425-23-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Software and Data Technologies - Volume 2: ICSOFT,
TI - APPROXIMATE REASONING BASED ON LINGUISTIC MODIFIERS IN A LEARNING SYSTEM
SN - 978-989-8425-23-2
AU - Bel Hadj Kacem S.
AU - Borgi A.
AU - Tagina M.
PY - 2010
SP - 431
EP - 437
DO - 10.5220/0002924204310437