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Subtopic in process mining.
Process mining is a technique used to turn event data into insights and actions. Techniques used in process mining such as Process discovery and Conformance checking depend only one the order of activities executed in the operations. The event log not only contains the activity details, but also timestamps, resources and data accompanied with process execution. Careful analysis of the external details from the event log can reveal useful information that can be used for making predictions on decisions that might be taken in the future (decision mining), efficiency and working dynamics of the team (organisational mining), and performance analysis.
Decision mining is a way of enhancing process models by analysing the decision points in the model and finding the rules in those decision points based on data attributes. The rules for decision mining is extracted using decision tree algorithms, that analyses decision points to find out which properties of a case might lead to taking certain paths in the process.[1][2]
^"Decision Mining in Business Processes" (PDF). BPM Center.
^van der Aalst, Wil M.P. (2008), Burstein, Frada; W. Holsapple, Clyde (eds.), "Decision Support Based on Process Mining", Handbook on Decision Support Systems 1: Basic Themes, International Handbooks Information System, Berlin, Heidelberg: Springer, pp. 637–657, doi:10.1007/978-3-540-48713-5_29, ISBN 978-3-540-48713-5, retrieved 2021-11-13
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