Abstract
n the field of process mining, the use of event logs for the purpose of root cause analysis is increasingly studied. In such an analysis, the availability of attributes/features that may explain the root cause of some phenomena is crucial. Currently, the process of obtaining these attributes from raw event logs is performed more or less on a case-by-case basis: there is still a lack of generalized systematic approach that captures this process. This paper proposes a systematic approach to enrich and transform event logs in order to obtain the required attributes for root cause analysis using classical data mining techniques, the classification techniques. This approach is formalized and its applicability has been validated using both self-generated and publicly-available logs.
Original language | English |
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Title of host publication | Business Process Management Workshops : BPM 2012 International Workshops, Tallinn, Estonia, September 3, 2012. Revised Papers |
Editors | M. La Rosa, P. Soffer |
Place of Publication | Berlin |
Publisher | Springer |
Pages | 174-186 |
ISBN (Print) | 978-3-642-36284-2 |
DOIs | |
Publication status | Published - 2013 |
Event | 8th International Workshop on Business Process Intelligence (BPI 2012) - Tallinn, Estonia Duration: 3 Sept 2012 → 3 Sept 2012 Conference number: 8 |
Publication series
Name | Lecture Notes in Business Information Processing |
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Volume | 132 |
ISSN (Print) | 1865-1348 |
Workshop
Workshop | 8th International Workshop on Business Process Intelligence (BPI 2012) |
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Abbreviated title | BPI 2012 |
Country/Territory | Estonia |
City | Tallinn |
Period | 3/09/12 → 3/09/12 |
Other | Workshop held in conjunction with the 10th International Conference on Business Process Management (BPM 2012) |