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Multi-Agents Approach for Data Mining Based k-Means for Improving the Decision Process in the ERP Systems

机译:基于数据挖掘的k-means的Multi-Agent方法改进ERP系统中的决策过程

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摘要

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.
机译:如今,企业资源计划(ERP)成为一种工具,可通过一个大型的单一数据库对公司的信息系统(IS)进行统一和一致的管理。另外,数据挖掘是一项旨在促进从大型数据库中提取信息和知识的技术。本文提出了一种基于代理的多层方法,通过ERP在k-Means上进行数据挖掘,以提取ERP数据库中的隐藏知识。为了实现这一目标,作者称多智能体系统的范例来分布称为智能体的几个自治实体的复杂性,其目标是使用专门用于聚类任务的k均值技术对相似对象类的记录或观察进行分组。 。通过使用多代理系统,这将有助于业务决策者做出正确的决策并提供非常好的响应时间。为了实现建议的体系结构,使用JADE平台更方便,同时提供一套完整的服务,并且代理符合FIPA规范。

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