مورد إلكتروني
A contextual approach to detecting synonymous and polluted activity labels in process event logs
| العنوان: | A contextual approach to detecting synonymous and polluted activity labels in process event logs |
|---|---|
| المؤلفون: | Panetto, Hervé, Debruyne, Christophe, Lewis, Dave, Hepp, Martin, Ardagna, Claudio Agostino, Meersman, Robert, Sadeghianasl, Sareh, ter Hofstede, Arthur, Wynn, Moe Thandar, Lim, Suriadi |
| المصدر: | On the Move to Meaningful Internet Systems: OTM 2019 Conferences: Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Proceedings (Lecture Notes in Computer Science, Volume 11877) |
| بيانات النشر: | Springer 2019 |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Process mining, as a well-established research area, uses algorithms for process-oriented data analysis. Similar to other types of data analysis, the existence of quality issues in input data will lead to unreliable analysis results (garbage in - garbage out). An important input for process mining is an event log which is a record of events related to a business process as it is performed through the use of an information system. While addressing quality issues in event logs is necessary, it is usually an ad-hoc and tiresome task. In this paper, we propose an automatic approach for detecting two types of data quality issues related to activities, both critical for the success of process mining studies: synonymous labels (same semantics with different syntax) and polluted labels (same semantics and same label structures). We propose the use of activity context, i.e. control flow, resource, time, and data attributes to detect semantically identical activity labels. We have implemented our approach and validated it using real-life logs from two hospitals and an insurance company, and have achieved promising results in detecting frequent imperfect activity labels. |
| مصطلحات الفهرس: | Activity Label, Data Quality, Process Event Log, Process Mining, Data quality, Activity label, Process event log, Chapter in Book, Report or Conference volume |
| URL: | doi:10.1007/978-3-030-33246-4_5 Sadeghianasl, Sareh, ter Hofstede, Arthur, Wynn, Moe Thandar, & Lim, Suriadi (2019) A contextual approach to detecting synonymous and polluted activity labels in process event logs. In Panetto, Hervé, Debruyne, Christophe, Lewis, Dave, Hepp, Martin, Ardagna, Claudio Agostino, & Meersman, Robert (Eds.) On the Move to Meaningful Internet Systems: OTM 2019 Conferences: Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Proceedings (Lecture Notes in Computer Science, Volume 11877). Springer, Switzerland, pp. 76-94. |
| الإتاحة: | Open access content. Open access content free_to_read http://creativecommons.org/licenses/by-nc/4.0 Consult author(s) regarding copyright matters This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au |
| ملاحظة: | application/pdf |
| أرقام أخرى: | ATUTQ oai:eprints.qut.edu.au:133873 Institute for Future Environments; Science & Engineering Faculty; School of Information Systems 1146608084 |
| المصدر المساهم: | QUEENSLAND UNIV OF TECH From OAIster®, provided by the OCLC Cooperative. |
| رقم الأكسشن: | edsoai.on1146608084 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |