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OrgMiner: A Framework for Discovering User-Related Process Intelligence from Event Logs
Information Systems Frontiers ( IF 5.9 ) Pub Date : 2020-04-08 , DOI: 10.1007/s10796-020-09990-7
Amit V. Deokar , Jie Tao

Process Intelligence refers to the extraction and analysis of valuable knowledge nuggets embedded in business process instances/event logs or enterprise applications, for the purpose of supporting various decision-making processes. Researchers and practitioners mine such event logs using Process Mining and Analytics (PMA) techniques that help analyze business processes across three perspectives: control flow, organization, and data. While previous PMA studies have made advances toward the control flow and data flow perspectives, there is limited research toward the organizational perspective of process intelligence. In this study, we propose an organizational mining framework, OrgMiner, that supports constructing organizational models from event logs. The framework utilizes the notion of behavioral patterns, which rely on the weak order relations appearing in event logs. The various modules and knowledge elements in the framework are described in detail. The components of the framework support identifying, selecting, and applying behavioral patterns using different metrics for organizational mining purposes. The derived organizational models can be used to support decision making in scenarios such as task assignment, resource allocation, as well as role-based access control. Compared to extant studies, the proposed approach does not assume prior availability of explicit process models. Additionally, the process patterns presented in this study can be used as building blocks, so that researchers and practitioners can use them directly or extend them further to identify complex organizational processes. A case study is presented to evaluate the feasibility and effectiveness of the OrgMiner framework.



中文翻译:

OrgMiner:从事件日志中发现与用户相关的流程智能的框架

流程智能是指提取和分析嵌入业务流程实例/事件日志或企业应用程序中的有价值的知识块,以支持各种决策流程。研究人员和从业人员使用流程挖掘和分析(PMA)技术来挖掘此类事件日志,该技术可从以下三个角度帮助分析业务流程:控制流,组织和数据。尽管先前的PMA研究在控制流和数据流方面取得了进步,但在过程智能的组织方面的研究却很少。在这项研究中,我们提出了一个组织挖掘框架OrgMiner,它支持从事件日志构造组织模型。该框架利用了行为模式的概念,该模式依赖于事件日志中出现的弱顺序关系。详细描述了框架中的各种模块和知识元素。框架的组件支持使用不同的指标来识别,选择和应用行为模式,以用于组织挖掘。派生的组织模型可用于支持任务分配,资源分配以及基于角色的访问控制等方案中的决策。与现有研究相比,所提出的方法没有假定显式过程模型的先验可用性。此外,本研究中介绍的过程模式可以用作构建模块,这样研究人员和从业人员就可以直接使用它们,或者进一步扩展它们以识别复杂的组织过程。提出了一个案例研究,以评估该方法的可行性和有效性。OrgMiner框架。

更新日期:2020-04-21
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