Privacy Aware Role Mining in Process mining
This project implements the decomposition method proposed in the paper Mining Roles From Event Logs While Preserving Privacy.
The implementation has been published as a standard Python package. Use the following command to install the corresponding Python package:
pip install pp-role-mining
from pp_role_mining.privacyPreserving import privacyPreserving #for fixed_value technique NoSubstitutions = 2 #for selective technique MinMax = [True, True] #if you want to perturb both lower and upper bound #for frequency_based technique FixedValue = 0 #to combine the fixed_value techniue with the frequency_based technique (FixedValue=0 is only frequency_based without any fixed value added to the number of substitutions) show_final_result = False event_log = "running_example.xes" # event_log = "pp_running_example.xes" technique = 'fixed_value' # fixed_value, selective, frequency_based resource_aware = True #true if we want to consider resources while allocating activity substitutions. Otherwise it is False hashedActivities = True #if you want to produce hash of activities exportPrivacyAwareLog = True #if you want to export the log with the perturbed activities privacy_aware_log_path = "pp_" + event_log # pp = privacyPreserving(event_log) pp.apply_privacyPreserving(technique, resource_aware, exportPrivacyAwareLog, show_final_result, hashedActivities, NoSubstitutions=NoSubstitutions, MinMax=MinMax, FixedValue=FixedValue, privacy_aware_log_path=privacy_aware_log_path, event_attribute2remove=["Activity", "Resource", "Costs"], case_attribute2remove=["creator"])
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