Process Mining
By Wil M.P. van der Aalst. Encyclopedia of Database Systems, 2009
1,186 citations recorded by the source corpus.
Subfields: Industrial and Manufacturing Engineering, Information Systems, Management Information Systems
View Paper: https://www.semanticscholar.org/paper/142376934370a24d7ab475928187b22c716fc0dd
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Industrial and Manufacturing Engineering
- Bernd Weber
- Manfred Reichert
- Mathias Weske
- Stefanie Rinderle-Ma
- Marlon Dumas
- Andrea Marrella
- Marcello La Rosa
- Massimo Mecella
In Information Systems
- Bernd Weber
- Manfred Reichert
- Wil M.P. van der Aalst
- J. Recker
- Jan Mendling
- Marlon Dumas
- Hajo Alexander Reijers
- Andrea Marrella
In Management Information Systems
- Wil M.P. van der Aalst
- Bernd Weber
- Manfred Reichert
- Jan Mendling
- J. Recker
- Hajo Alexander Reijers
- Marlon Dumas
- Andrea Marrella
Citations in the corpus
- Automated Discovery of Process Models from Event Logs: Review and Benchmark (2017, methodology): “Specifically, the process model discovered from an event log should: (i) parse the traces in the log; (ii) parse traces that are not in the log but are likely to belong to the process that produced the log; and (iii) not parse other traces [2].”
- Responsible Data Science (2017, background): “In van der Aalst (2016a) the term ‘‘green data science’’ was coined for cutting-edge solutions that enable individuals, organizations, and society to benefit from widespread data availability while ensuring Fairness, Accuracy, Confidentiality, and Transparency.”
- Blockchains for Business Process Management - Challenges and Opportunities (2017, methodology): “These pieces of information can be used to discover real processes, detect deviations, and conduct root cause analysis [1], ranging over small groups of companies or over an industry at large.”