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Local Concurrency Detection in Business Process Event Logs
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| Zeitschriftentitel: | ACM Transactions on Internet Technology |
|---|---|
| Personen und Körperschaften: | , , , |
| In: | ACM Transactions on Internet Technology, 19, 2019, 1, S. 1-23 |
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Association for Computing Machinery (ACM)
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Armas-Cervantes, Abel Dumas, Marlon Rosa, Marcello La Maaradji, Abderrahmane Armas-Cervantes, Abel Dumas, Marlon Rosa, Marcello La Maaradji, Abderrahmane |
|---|---|
| author |
Armas-Cervantes, Abel Dumas, Marlon Rosa, Marcello La Maaradji, Abderrahmane |
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Armas-Cervantes, Abel Dumas, Marlon Rosa, Marcello La Maaradji, Abderrahmane ACM Transactions on Internet Technology Local Concurrency Detection in Business Process Event Logs Computer Networks and Communications |
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Armas-Cervantes, Abel Dumas, Marlon Rosa, Marcello La Maaradji, Abderrahmane 1533-5399 1557-6051 Association for Computing Machinery (ACM) Computer Networks and Communications http://dx.doi.org/10.1145/3289181 <jats:p>Process mining techniques aim at analyzing records generated during the execution of a business process in order to provide insights on the actual performance of the process. Detecting concurrency relations between events is a fundamental primitive underpinning a range of process mining techniques. Existing approaches to this problem identify concurrency relations at the level of event types under a global interpretation. If two event types are declared to be concurrent, every occurrence of one event type is deemed to be concurrent to one occurrence of the other. In practice, this interpretation is too coarse-grained and leads to over-generalization. This article proposes a finer-grained approach, whereby two event types may be deemed to be in a concurrency relation relative to one state of the process, but not relative to other states. In other words, the detected concurrency relation holds locally, relative to a set of states. Experimental results both with artificial and real-life logs show that the proposed local concurrency detection approach improves the accuracy of existing concurrency detection techniques.</jats:p> Local Concurrency Detection in Business Process Event Logs ACM Transactions on Internet Technology |
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| title |
Local Concurrency Detection in Business Process Event Logs |
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Local Concurrency Detection in Business Process Event Logs |
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Local Concurrency Detection in Business Process Event Logs |
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Local Concurrency Detection in Business Process Event Logs |
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Local Concurrency Detection in Business Process Event Logs |
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local concurrency detection in business process event logs |
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Computer Networks and Communications |
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2019 |
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1-23 |
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<jats:p>Process mining techniques aim at analyzing records generated during the execution of a business process in order to provide insights on the actual performance of the process. Detecting concurrency relations between events is a fundamental primitive underpinning a range of process mining techniques. Existing approaches to this problem identify concurrency relations at the level of event types under a global interpretation. If two event types are declared to be concurrent, every occurrence of one event type is deemed to be concurrent to one occurrence of the other. In practice, this interpretation is too coarse-grained and leads to over-generalization. This article proposes a finer-grained approach, whereby two event types may be deemed to be in a concurrency relation relative to one state of the process, but not relative to other states. In other words, the detected concurrency relation holds locally, relative to a set of states. Experimental results both with artificial and real-life logs show that the proposed local concurrency detection approach improves the accuracy of existing concurrency detection techniques.</jats:p> |
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| author | Armas-Cervantes, Abel, Dumas, Marlon, Rosa, Marcello La, Maaradji, Abderrahmane |
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| description | <jats:p>Process mining techniques aim at analyzing records generated during the execution of a business process in order to provide insights on the actual performance of the process. Detecting concurrency relations between events is a fundamental primitive underpinning a range of process mining techniques. Existing approaches to this problem identify concurrency relations at the level of event types under a global interpretation. If two event types are declared to be concurrent, every occurrence of one event type is deemed to be concurrent to one occurrence of the other. In practice, this interpretation is too coarse-grained and leads to over-generalization. This article proposes a finer-grained approach, whereby two event types may be deemed to be in a concurrency relation relative to one state of the process, but not relative to other states. In other words, the detected concurrency relation holds locally, relative to a set of states. Experimental results both with artificial and real-life logs show that the proposed local concurrency detection approach improves the accuracy of existing concurrency detection techniques.</jats:p> |
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| spelling | Armas-Cervantes, Abel Dumas, Marlon Rosa, Marcello La Maaradji, Abderrahmane 1533-5399 1557-6051 Association for Computing Machinery (ACM) Computer Networks and Communications http://dx.doi.org/10.1145/3289181 <jats:p>Process mining techniques aim at analyzing records generated during the execution of a business process in order to provide insights on the actual performance of the process. Detecting concurrency relations between events is a fundamental primitive underpinning a range of process mining techniques. Existing approaches to this problem identify concurrency relations at the level of event types under a global interpretation. If two event types are declared to be concurrent, every occurrence of one event type is deemed to be concurrent to one occurrence of the other. In practice, this interpretation is too coarse-grained and leads to over-generalization. This article proposes a finer-grained approach, whereby two event types may be deemed to be in a concurrency relation relative to one state of the process, but not relative to other states. In other words, the detected concurrency relation holds locally, relative to a set of states. Experimental results both with artificial and real-life logs show that the proposed local concurrency detection approach improves the accuracy of existing concurrency detection techniques.</jats:p> Local Concurrency Detection in Business Process Event Logs ACM Transactions on Internet Technology |
| spellingShingle | Armas-Cervantes, Abel, Dumas, Marlon, Rosa, Marcello La, Maaradji, Abderrahmane, ACM Transactions on Internet Technology, Local Concurrency Detection in Business Process Event Logs, Computer Networks and Communications |
| title | Local Concurrency Detection in Business Process Event Logs |
| title_full | Local Concurrency Detection in Business Process Event Logs |
| title_fullStr | Local Concurrency Detection in Business Process Event Logs |
| title_full_unstemmed | Local Concurrency Detection in Business Process Event Logs |
| title_short | Local Concurrency Detection in Business Process Event Logs |
| title_sort | local concurrency detection in business process event logs |
| title_unstemmed | Local Concurrency Detection in Business Process Event Logs |
| topic | Computer Networks and Communications |
| url | http://dx.doi.org/10.1145/3289181 |