%0 Conference Proceedings
%T Association Rules Algorithms for Data Mining Process Based on Multi Agent System
%+ Université Mohammed Premier [Oujda]
%+ Université Sidi Mohamed Ben Abdellah (USMBA)
%A Belabed, Imane
%A Talibi Alaoui, Mohammed
%A El Miloud, Jaara
%A Belabed, Abdelmajid
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 2nd International Conference on Machine Learning for Networking (MLN)
%C Paris, France
%Y Selma Boumerdassi
%Y Éric Renault
%Y Paul Mühlethaler
%I Springer International Publishing
%3 Machine Learning for Networking
%V LNCS-12081
%P 431-443
%8 2019-12-03
%D 2019
%R 10.1007/978-3-030-45778-5_30
%K Association rules
%K Apriori
%K Clustering
%K Multi agent system
%K Genetic algorithm
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X In this paper, we present a collaborative multi-agent based system for data mining. We have used two data mining model functions, clustering of variables in order to build homogeneous groups of attributes, association rules inside each of these groups and a multi-agent approach to integrate the both data mining techniques. For the association rules extraction, we use both apriori algorithm and genetic algorithm.The main goal of this paper is the evaluation of the association rules obtained by running apriori and genetic algorithm using quantitative datasets in multi agent environment.
%G English
%Z TC 6
%2 https://inria.hal.science/hal-03266467/document
%2 https://inria.hal.science/hal-03266467/file/487577_1_En_30_Chapter.pdf
%L hal-03266467
%U https://inria.hal.science/hal-03266467
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC6
%~ IFIP-LNCS-12081
%~ IFIP-MLN