首页> 外文期刊>Expert Systems with Application >Process mining techniques and applications - A systematic mapping study
【24h】

Process mining techniques and applications - A systematic mapping study

机译:流程挖掘技术和应用-系统映射研究

获取原文
获取原文并翻译 | 示例
           

摘要

Process mining is a growing and promising study area focused on understanding processes and to help capture the more significant findings during real execution rather than, those methods that, only observed idealized process model. The objective of this article is to map the active research topics of process mining and their main publishers by country, periodicals, and conferences. We also extract the reported application studies and classify these by exploration domains or industry segments that are taking advantage of this technique. The applied research method was systematic mapping, which began with 3713 articles. After applying the exclusion criteria, 1278 articles were selected for review. In this article, an overview regarding process mining is presented, the main research topics are identified, followed by identification of the most applied process mining algorithms, and finally application domains among different business segments are reported on. It is possible to observe that the most active research topics are associated with the process discovery algorithms, followed by conformance checking, and architecture and tools improvements. In application domains, the segments with major case studies are healthcare followed by information and communication technology, manufacturing, education, finance, and logistics. (C) 2019 Elsevier Ltd. All rights reserved.
机译:流程挖掘是一个不断发展的,充满希望的研究领域,致力于了解流程并帮助在实际执行过程中捕获更重要的发现,而不是仅观察理想流程模型的那些方法。本文的目的是按国家,期刊和会议来概述过程挖掘及其主要发行者的活跃研究主题。我们还将提取已报告的应用研究,并根据利用该技术的勘探领域或行业细分进行分类。应用的研究方法是系统映射,从3713篇文章开始。应用排除标准后,选择了1278篇文章进行审查。在本文中,将介绍有关流程挖掘的概述,确定主要的研究主题,然后确定最常用的流程挖掘算法,最后报告不同业务部门之间的应用领域。可以观察到,最活跃的研究主题与过程发现算法相关联,其次是一致性检查以及体系结构和工具改进。在应用领域,主要案例研究的领域是医疗保健,其次是信息和通信技术,制造,教育,金融和物流。 (C)2019 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号