论文标题
发现业务领域效应以使用聚类和影响分析处理采矿分析
Discovering Business Area Effects to Process Mining Analysis Using Clustering and Influence Analysis
论文作者
论文摘要
改善大型组织业务流程的一个普遍挑战是，负责运营的商人缺乏对执行细节，过程变体和业务运营中发生的例外的理解。尽管现有的流程挖掘方法可以根据事件日志发现这些详细信息，但将流程挖掘发现与商人传达是挑战。在本文中，我们提出了一种新的方法，用于发现对流程执行细节产生重大影响的业务领域。我们的方法使用聚类基于过程流量特征将类似情况分组，然后影响分析，以检测与发现的群集最相关的业务领域。我们的分析是BPM人与企业之间的桥梁，人们促进了这些群体之间的知识共享。我们还基于公开可用的现实生活购买订单流程数据提供了示例分析。
A common challenge for improving business processes in large organizations is that business people in charge of the operations are lacking a fact-based understanding of the execution details, process variants, and exceptions taking place in business operations. While existing process mining methodologies can discover these details based on event logs, it is challenging to communicate the process mining findings to business people. In this paper, we present a novel methodology for discovering business areas that have a significant effect on the process execution details. Our method uses clustering to group similar cases based on process flow characteristics and then influence analysis for detecting those business areas that correlate most with the discovered clusters. Our analysis serves as a bridge between BPM people and business, people facilitating the knowledge sharing between these groups. We also present an example analysis based on publicly available real-life purchase order process data.
