Szczegóły publikacji
Opis bibliograficzny
Conformance checking for time-series-aware processes / Victor Rodriguez-Fernandez, Agnieszka TRZCIONKOWSKA, Antonio Gonzalez-Pardo, Edyta BRZYCHCZY, Grzegorz J. NALEPA, David Camacho // IEEE Transactions on Industrial Informatics ; ISSN 1551-3203. — 2021 — vol. 17 no. 2 art. no. 9018187, s. 871-881. — Bibliogr. s. 880-881, Abstr. — Publikacja dostępna online od: 2020-02-28. — Grzegorz J. Nalepa - dod. afiliacja: Jagiellonian University, Kraków, Poland
Autorzy (6)
- Rodriguez-Fernandez Victor
- AGHŻuber Agnieszka
- Gonzalez-Pardo Antonio
- AGHBrzychczy Edyta
- AGHNalepa Grzegorz Jacek
- Camacho David
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 131159 |
|---|---|
| Data dodania do BaDAP | 2020-11-30 |
| Tekst źródłowy | URL |
| DOI | 10.1109/TII.2020.2977126 |
| Rok publikacji | 2021 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | IEEE Transactions on Industrial Informatics |
Abstract
This article tackles the problem of checking the conformance between a business process model and the data produced by its execution in cases where the data are not given as an event log, but as a set of time series containing the evolution of the variables involved in the process. Tasks in the process model are no longer restricted to the occurrence of a single event, and instead, they can be expressed as a set of temporal conditions about the values of the variables in the log. This causes a paradigm shift in conformance checking (and process mining at a more general level), and because of this, the formalization of both the data and the process model and the algorithms are here redesigned and adapted for this challenging perspective. To illustrate the effectiveness of our approach, an experimental evaluation on a real-world time-series log is carried out, highlighting the benefits of this change of paradigm.