A new approach agent-based for distributing association rules by business to improve decision process in ERP systems

Merouane Zoubeidi, Okba Kazar, Saber Benharzallah, Nadjib Mesbahi, Abdelhak Merizig and Djamil Rezki

International Journal of Information and Decision Sciences, 2020, vol. 12, issue 1, 1-35

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.

Keywords: enterprise resource planning; ERP; multi-agents system; MAS; data mining associate rules; JADE; WEKA. (search for similar items in EconPapers)
Date: 2020
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