Laboratoire de Génie Informatique et d’Automatique de l’Artois

Ahmed SAMET

Ph.D. student
(Position when this person departed from the LGI2A)
Member of the research themes:

Revue Internationale avec Comité de Lecture

Ahmed SAMET -- Eric LEFEVRE -- Sadok BEN YAHIA
Evidential data mining: precise support and confidence
Journal of Intelligent Information Systems, pp 135-163, Vol. 47, No. 1, 06/2016
2015
International journal with review committee
Reliability estimation measure: Generic discounting approach
International Journal of Pattern Recognition and Artificial Intelligence, IJPRAI, pp 1559011 , Vol. 29, No. 7, 11/2015
Ahmed SAMET -- Eric LEFEVRE -- Sadok BEN YAHIA
Integration of extra-information for belief function theory conflict management problem through generic association rules
International Journal of Uncertainty, Fuzziness and Knowledge-based Systems, IJUFKS, pp 531-551, Vol. 22, No. 4, 08/2014

Conférence Internationale avec Comité de Lecture

2015
International conference with review committee
Issam NOUAOURI -- Ahmed SAMET -- Hamid ALLAOUI
Evidential Data Mining for Length of Stay (LOS) Prediction Problem
IEEE International Conference on Automation Science and Engineering, CASE2015, Gothenburg, Sweden, 08/2015
2014
International conference with review committee
Ahmed SAMET -- Eric LEFEVRE -- Sadok BEN YAHIA
Belief function classification with conflict management: application on forest image
10th International conference on Signal-Image Technology and internet-based systems, SITIS, pp 14-20, 11/2014
Ahmed SAMET -- Eric LEFEVRE -- Sadok BEN YAHIA
Evidential database: a new generalization of database?
3rd International Conference on Belief Functions, BELIEF 2014, pp 105-114, Oxford, United Kingdom, F. Cuzzolin (Ed.), 09/2014
2014
International conference with review committee
Ahmed SAMET -- Eric LEFEVRE -- Sadok BEN YAHIA
Classification with evidential associative rules
15th Information Processing and Management of Uncertainty in Knowledge-Based Systems International Conference, IPMU 2014, pp 25-35, Montpellier, France, 07/2014
2013
International conference with review committee
Ahmed SAMET -- Eric LEFEVRE -- Sadok BEN YAHIA
Mining frequent itemsets in evidential database
5th International conference on Knowledge and Systems Engineering, KSE'2013, pp 377-388, Vol. 245, Springer-Verlag, Advances in Intelligent Systems and Comp, 10/2013
2013
International conference with review committee
Ahmed SAMET -- Imen HAMMAMI -- Eric LEFEVRE -- Atef HAMOUDA
Generic discounting avaluation approach for urban image classification
3rd international symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM'2013, pp 79-90, 07/2013
2013
International conference with review committee
Ahmed SAMET -- Eric LEFEVRE -- Sadok BEN YAHIA
Reliability estimation with extrinsic measure in belief function theory
5 th International Conference on Modeling, Simulation and Applied Optimization, ICMSAO'2013, pp 1-6, 04/2013
2011
International conference with review committee
Classificationof high-resolution remote sensing image by adapting the distance belief function estimation model
International Conference on Communications, Computing and Control Applications , CCCA'2011, pp 1-6, Hammamet, Tunisie, 03/2011

Author of the Ph.D. thesis "Belief function theory : application of data mining tools for imperfect data treatment"

2011 - 2014

This thesis explores the relation between two domains which are the Belief Function Theory (BFT) and data mining. Two main interactions between those domain have been pointed out.The first interaction studies the contribution of the generic associative rules in the BFT. We were interested in managing conflict in case of fusing conflictual information sources. A new approach for conflict management based on generic association rules has been proposed called ACM.The second interation studies imperfect databases such as evidential databases. Those kind of databases, where information is represented by belief functions, are studied in order to extract hidden knowledges using data mining tools. The extraction of those knowledges was possible thanks to a new definition to the support and the confidence measures. Those measures were integrated into a new evidential associative classifier called EDMA.