A Framework of Business Process Monitoring and Prediction Techniques

被引:0
|
作者
Wolf, Frederik [1 ]
Brunk, Jens [1 ]
Becker, Joerg [1 ]
机构
[1] Univ Munster ERCIS, Munster, Germany
关键词
Business process; Prediction; Techniques; Predictive Business Process Monitoring;
D O I
10.1007/978-3-030-86797-3_47
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The digitization of businesses provides huge amounts of data that can be leveraged by modern Business ProcessManagement methods. Predictive Business ProcessMonitoring (PBPM) represents techniques which deal with real-time analysis of currently running process instances and alsowith the prediction of their future behavior. While many different prediction techniques have been developed, most of the early techniques base their predictions solely on the controlfow characteristic of a business process. More recently, researchers attempt to incorporate additional process-related information, also known as the process context, into their predictive models. In 2018, Di Francescomarino et al. published a framework of existing prediction techniques. Since the young field has evolved greatly since then and context information continue to play a greater role in predictive techniques, this paper describes the process and outcome of updating and extending the framework to include process context dimensions by replicating the literature review of the initial authors.
引用
收藏
页码:714 / 724
页数:11
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