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文章基本信息

  • 标题:Framework to Enhance ERP Usability by Machine Learning Based Requirements Prioritization
  • 本地全文:下载
  • 作者:Shamaila Qayyum ; Almas Abbasi
  • 期刊名称:Journal of Software
  • 印刷版ISSN:1796-217X
  • 出版年度:2017
  • 卷号:12
  • 期号:8
  • 页码:664-670
  • DOI:10.17706/jsw.12.8.664-670
  • 出版社:Academy Publisher
  • 摘要:With the growing trend of technology and increased business needs, Enterprise Resource Planning (ERP) systems are verily adapted by many organizations. Despite all the promising benefits and use, ERPs cannot always be successful. It has been established that ERP’s success is measured in terms of its’ users’ satisfaction. Different models exist, that show how Information systems’ success can be achieved. This paper focuses on the idea that machine learning helps in flawless prioritization of requirements and thus results in high user satisfaction. The paper proposes an IS success framework that incorporates machine learning based requirements prioritization techniques in order to increase users’ satisfaction for making an ERP, a successful project.
  • 其他关键词:ERP, Machine Learning, Requirements Prioritization, User Satisfaction
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