Fairness-Aware Process Mining

被引:9
|
作者
Qafari, Mahnaz Sadat [1 ]
van der Aalst, Wil [1 ]
机构
[1] Rhein Westfal TH Aachen RWTH, Aachen, Germany
来源
ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS: OTM 2019 CONFERENCES | 2019年 / 11877卷
关键词
D O I
10.1007/978-3-030-33246-4_11
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Process mining is a multi-purpose tool enabling organizations to improve their processes. One of the primary purposes of process mining is finding the root causes of performance or compliance problems in processes. The usual way of doing so is by gathering data from the process event log and other sources and then applying some data mining and machine learning techniques. However, the results of applying such techniques are not always acceptable. In many situations, this approach is prone to making obvious or unfair diagnoses and applying them may result in conclusions that are unsurprising or even discriminating. In this paper, we present a solution to this problem by creating a fair classifier for such situations. The undesired effects are removed at the expense of reduction on the accuracy of the resulting classifier.
引用
收藏
页码:182 / 192
页数:11
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