Abstract
New and compelling regulations (e.g., the GDPR in Europe) impose tremendous pressure on organizations, in order to adhere to standard procedures, processes, and practices. The field of conformance checking aims to quantify the extent to which the execution of a process, captured within recorded corresponding event data, conforms to a given reference process model. Existing techniques assume a post-mortem scenario, i.e. they detect deviations based on complete executions of the process. This limits their applicability in an online setting. In such context, we aim to detect deviations online (i.e., in-vivo), in order to provide recovery possibilities before the execution of a process instance is completed. Also, current techniques assume cases to start from the initial stage of the process, whereas this assumption is not feasible in online settings. In this paper, we present a generic framework for online conformance checking, in which the underlying process is represented in terms of behavioural patterns and no assumption on the starting point of cases is needed. We instantiate the framework on the basis of Petri nets, with an accompanying new unfolding technique. The approach is implemented in the process mining tool ProM, and evaluated by means of several experiments including a stress-test and a comparison with a similar technique.
| Original language | English |
|---|---|
| Title of host publication | Business Process Management - 16th International Conference, BPM 2018, Proceedings |
| Editors | Marco Montali, Ingo Weber, Mathias Weske, Jan vom Brocke |
| Place of Publication | Cham |
| Publisher | Springer |
| Pages | 250-267 |
| Number of pages | 18 |
| ISBN (Electronic) | 978-3-319-98648-7 |
| ISBN (Print) | 978-3-319-98647-0 |
| DOIs | |
| Publication status | Published - 1 Jan 2018 |
| Event | 16th International Conference on Business Process Management, BPM 2018 - Sydney, Australia Duration: 9 Sep 2018 → 14 Sep 2018 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11080 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 16th International Conference on Business Process Management, BPM 2018 |
|---|---|
| Country | Australia |
| City | Sydney |
| Period | 9/09/18 → 14/09/18 |
Fingerprint
Keywords
- Behavioural patterns
- Conformance checking
- Online processing
- Petri nets
- Stream processing
- Unfoldings
Cite this
}
Online conformance checking using behavioural patterns. / Burattin, Andrea; van Zelst, Sebastiaan J.; Armas-Cervantes, Abel; van Dongen, Boudewijn F.; Carmona, Josep.
Business Process Management - 16th International Conference, BPM 2018, Proceedings. ed. / Marco Montali; Ingo Weber; Mathias Weske; Jan vom Brocke. Cham : Springer, 2018. p. 250-267 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11080 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Online conformance checking using behavioural patterns
AU - Burattin, Andrea
AU - van Zelst, Sebastiaan J.
AU - Armas-Cervantes, Abel
AU - van Dongen, Boudewijn F.
AU - Carmona, Josep
PY - 2018/1/1
Y1 - 2018/1/1
N2 - New and compelling regulations (e.g., the GDPR in Europe) impose tremendous pressure on organizations, in order to adhere to standard procedures, processes, and practices. The field of conformance checking aims to quantify the extent to which the execution of a process, captured within recorded corresponding event data, conforms to a given reference process model. Existing techniques assume a post-mortem scenario, i.e. they detect deviations based on complete executions of the process. This limits their applicability in an online setting. In such context, we aim to detect deviations online (i.e., in-vivo), in order to provide recovery possibilities before the execution of a process instance is completed. Also, current techniques assume cases to start from the initial stage of the process, whereas this assumption is not feasible in online settings. In this paper, we present a generic framework for online conformance checking, in which the underlying process is represented in terms of behavioural patterns and no assumption on the starting point of cases is needed. We instantiate the framework on the basis of Petri nets, with an accompanying new unfolding technique. The approach is implemented in the process mining tool ProM, and evaluated by means of several experiments including a stress-test and a comparison with a similar technique.
AB - New and compelling regulations (e.g., the GDPR in Europe) impose tremendous pressure on organizations, in order to adhere to standard procedures, processes, and practices. The field of conformance checking aims to quantify the extent to which the execution of a process, captured within recorded corresponding event data, conforms to a given reference process model. Existing techniques assume a post-mortem scenario, i.e. they detect deviations based on complete executions of the process. This limits their applicability in an online setting. In such context, we aim to detect deviations online (i.e., in-vivo), in order to provide recovery possibilities before the execution of a process instance is completed. Also, current techniques assume cases to start from the initial stage of the process, whereas this assumption is not feasible in online settings. In this paper, we present a generic framework for online conformance checking, in which the underlying process is represented in terms of behavioural patterns and no assumption on the starting point of cases is needed. We instantiate the framework on the basis of Petri nets, with an accompanying new unfolding technique. The approach is implemented in the process mining tool ProM, and evaluated by means of several experiments including a stress-test and a comparison with a similar technique.
KW - Behavioural patterns
KW - Conformance checking
KW - Online processing
KW - Petri nets
KW - Stream processing
KW - Unfoldings
UR - http://www.scopus.com/inward/record.url?scp=85053638640&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-98648-7_15
DO - 10.1007/978-3-319-98648-7_15
M3 - Conference contribution
AN - SCOPUS:85053638640
SN - 978-3-319-98647-0
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 250
EP - 267
BT - Business Process Management - 16th International Conference, BPM 2018, Proceedings
A2 - Montali, Marco
A2 - Weber, Ingo
A2 - Weske, Mathias
A2 - vom Brocke, Jan
PB - Springer
CY - Cham
ER -