Metadata-Version: 2.1
Name: p-connector-dfg
Version: 0.0.13
Summary: Privacy-preserving Process Discovery Using Connector Method
Home-page: https://github.com/m4jidRafiei/privacyAware-ConnectorMethod_DFG
Author: Majid Rafiei
Author-email: majid.rafiei@pads.rwth-aachen.de
License: GPL 3.0
Project-URL: Source, https://github.com/m4jidRafiei/privacyAware-ConnectorMethod_DFG
Description: ## Introduction
        This project implements the connector method proposed in the paper [Supporting Confidentiality in Process Mining Using Abstraction and Encryption](https://www.researchgate.net/publication/338432872_Supporting_Confidentiality_in_Process_Mining_Using_Abstraction_and_Encryption) and [Ensuring Confidentiality in Process Mining](https://www.researchgate.net/publication/330042256_Ensuring_Confidentiality_in_Process_Mining).
        ## Python package
        The implementation has been published as a standard Python package. Use the following command to install the corresponding Python package:
        
        ```shell
        pip install p-connector-dfg
        ```
        
        ## Usage
        
        ```python
        from p_connector_dfg.privacyPreserving import privacyPreserving
        
        ela_path = ".\intermediate_results\ela_connector.xml"
        ela_method = "Connector Method"
        ela_desired_analyses = ['directly follows graph', 'process discovery']
        
        activity_activity_matrix_path = r".\intermediate_results\test.csv"
        
        dfg_path = "./DFG.svg"
        freq_threshold = 0.0
        
        #Connector structure parameters--------------
        relation_depth = True #if you want to have relation depth in the connector structure
        trace_length = True # if you want to have trace length in the connector structure
        trace_id = True # if you want to have a fake trace id in the connector structure
        
        event_log = "sample_log.xes"
        key = 'DEFPASSWORD12345'
        
        pp = privacyPreserving(event_log)
        pp.apply_privacyPreserving(key, ela_path, ela_method, ela_desired_analyses, event_log, relation_depth = relation_depth, trace_length = trace_length, trace_id = trace_id)
        
        pp.result_maker_ela(ela_path, True,True, True, freq_threshold, dfg_path, activity_activity_matrix_path = activity_activity_matrix_path,key = key)
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
