Process Activity Ontology Learning From Event Logs Through Gamification

被引:3
|
作者
Sadeghianasl, Sareh [1 ]
Ter Hofstede, Arthur H. M. [1 ]
Wynn, Moe Thandar [1 ]
Turkay, Selen [2 ]
Myers, Trina [1 ]
机构
[1] Queensland Univ Technol, Sch Informat Syst, Brisbane, Qld 4000, Australia
[2] Queensland Univ Technol, Sch Comp Sci, Brisbane, Qld 4000, Australia
来源
IEEE ACCESS | 2021年 / 9卷
关键词
Ontologies; Semantics; Task analysis; Crowdsourcing; OWL; Resource description framework; Data mining; Process mining; activity labels; ontology; data quality; gamification; crowdsourcing; SEMANTIC WEB; GENERATION; CHOICE; GAMES; FLOW;
D O I
10.1109/ACCESS.2021.3134915
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Process mining is concerned with deriving knowledge from process data as recorded in so-called event logs. The quality of event logs is a constraining factor in achieving reliable insights. Particular quality problems are posed by activity labels which are meant to be representative of organisational activities, but may take different manifestations (e.g. as a result of manual entry synonyms may be introduced). Ideally, such problems are remedied by domain experts, but they are time-poor and data cleaning is a time-consuming and tedious task. Ontologies provide a means to formalise domain knowledge and their use can provide a scalable solution to fixing activity label similarity problems, as they can be extended and reused over time. Existing approaches to activity label quality improvement use manually-generated ontologies or ontologies that are too general (e.g. WordNet). Limited attention has been paid to facilitating the development of purposeful ontologies in the field of process mining. This paper is concerned with the creation of activity ontologies by domain experts. For the first time in the field of process mining, their participation is facilitated and motivated through the application of techniques from crowdsourcing and gamification. Evaluation of our approach to the construction of activity ontologies by 35 participants shows that they found the method engaging and that its application results in high-quality ontologies.
引用
收藏
页码:165865 / 165880
页数:16
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