Interactive Process Drift Detection Framework

被引:2
|
作者
Vecino Sato, Denise Maria [1 ,2 ]
Barddal, Jean Paul [1 ]
Scalabrin, Edson Emilio [1 ]
机构
[1] Pontifical Catholic Univ Parana PUCPR, Imac Conceicao 1155, BR-80215901 Curitiba, Parana, Brazil
[2] Fed Inst Parana IFPR, Joao Negrao 1285, BR-80230150 Curitiba, Parana, Brazil
来源
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING (ICAISC 2021), PT II | 2021年 / 12855卷
关键词
Process drift; Concept drift; Drift detection; Evolving environment;
D O I
10.1007/978-3-030-87897-9_18
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a novel tool for detecting drifts in process models. The tool targets the challenge of defining the better parameter configuration for detecting drifts by providing an interactive user interface. Using this interface, the user can quickly change the parameters and verify how the process evolved. The process evolution is presented in a timeline of process models, simulating a "replay" of models over time. One instantiation of the framework was implemented using a fixed-size sliding window, discovering process maps using directly-follows graphs (DFGs), and calculating nodes and edges similarities. This instantiation was evaluated using a benchmarking dataset of simple and complex drift patterns. The tool correctly detected 17 from the 18 change patterns, thus confirming its potential when an adequate window size is set. The user interface shows that replaying the process models provides a visual understanding of the changing process. The concept drift is explained by the similarity metrics' differences, thus allowing drift localization.
引用
收藏
页码:192 / 204
页数:13
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