Paper Info
Title
Multi-Agents Approach for Data Mining Based k-Means for Improving the Decision Process in the ERP Systems
Abstract
Today the enterprise resource planning ERP became a tool that enables uniform and consistent management of information system IS of the company with a large single database. In addition, Data Mining is a technology whose purpose is to promote information and knowledge extraction from a large database. In this paper, an agent-based multi-layered approach for data mining based k-Means through the ERP to extract hidden knowledge in the ERP database is proposed. To achieve this, the authors call the paradigm of multi-agent system to distribute the complexity of several autonomous entities called agents, whose goal is to group records or observations on similar objects classes using the k-means technique that is dedicated the task of clustering. This will help business decision-makers to take good decisions and provide a very good response time by the use of multi-agent system. To implement the proposed architecture, it is more convenient to use the JADE platform while providing a complete set of services and agents comply with the specifications FIPA.
Year
DOI
Venue
2015
10.4018/IJDSST.2015040101
IJDSST
Keywords
Field
DocType
Data Mining, Enterprise Resource Planning (ERP), JADE, K-Means, Multi-Agents System (MAS)
Information system,k-means clustering,Data mining,Architecture,Enterprise resource planning,Computer science,Response time,Knowledge extraction,Decision process,Cluster analysis
Journal
Volume
Issue
ISSN
7
2
1941-6296
Citations 
PageRank 
References 
3
1.09
3
Authors
5
Name
Order
Citations
PageRank
Nadjib Mesbahi142.49
Okba Kazar21422.61
Benharzallah Saber366.58
Merouane Zoubeidi432.44
Samir Bourekkache5116.64