A new approach agent-based for distributing association rules by business to improve decision process in ERP systems
by Merouane Zoubeidi; Okba Kazar; Saber Benharzallah; Nadjib Mesbahi; Abdelhak Merizig; Djamil Rezki
International Journal of Information and Decision Sciences (IJIDS), Vol. 12, No. 1, 2020

Abstract: Nowadays, the distributed computing plays an important role in the data mining process. To make systems scalable it is important to develop mechanisms that distribute the workload among several sites in a flexible way. Moreover, the acronym ERP refers to the systems and software packages used by organisations to manage day-by-day business activities. ERP systems are designed for the defined schema that usually has a common database. In this paper, we present a collaborative multi-agent based system for association rules mining from distributed databases. In our proposed approach, we combine the multi-agent system with association rules as a data mining technique to build a model that can execute the association rules mining in a parallel and distributed way from the centralised ERP database. The autonomous agents used to provide a generic and scalable platform. This will help business decision-makers to take the right decisions and provide a perfect response time using multi-agent system. The platform has been compared with the classic association rules algorithms and has proved to be more efficient and more scalable.

Online publication date: Mon, 10-Feb-2020

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