Aligning Event Logs and Process Models for Multi-perspective Conformance Checking: An Approach Based on Integer Linear Programming

2013 ◽  
pp. 113-129 ◽  
Author(s):  
Massimiliano de Leoni ◽  
Wil M. P. van der Aalst
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Process Models ◽  
Conformance Checking ◽  
Event Logs

scholarly journals Business process mining

2017 ◽  
Vol 01 (01) ◽  
pp. 1630004 ◽  
Author(s):  
Asef Pourmasoumi ◽  
Ebrahim Bagheri
Keyword(s):  
Process Mining ◽  
Status Quo ◽  
Process Models ◽  
Added Value ◽  
Conformance Checking ◽  
Event Logs ◽  
Organizational Information ◽  
Organization Process ◽  
The Status ◽  
Business Process Mining

One of the most valuable assets of an organization is its organizational data. The analysis and mining of this potential hidden treasure can lead to much added-value for the organization. Process mining is an emerging area that can be useful in helping organizations understand the status quo, check for compliance and plan for improving their processes. The aim of process mining is to extract knowledge from event logs of today’s organizational information systems. Process mining includes three main types: discovering process models from event logs, conformance checking and organizational mining. In this paper, we briefly introduce process mining and review some of its most important techniques. Also, we investigate some of the applications of process mining in industry and present some of the most important challenges that are faced in this area.

Aligning Event Logs and Declarative Process Models for Conformance Checking

2012 ◽  
pp. 82-97 ◽  
Author(s):  
Massimiliano de Leoni ◽  
Fabrizio Maria Maggi ◽  
Wil M. P. van der Aalst
Keyword(s):  
Process Models ◽  
Conformance Checking ◽  
Event Logs

scholarly journals Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance

2018 ◽  
Vol 15 (12) ◽  
pp. 2809 ◽  
Author(s):  
Christoph Rinner ◽  
Emmanuel Helm ◽  
Reinhold Dunkl ◽  
Harald Kittler ◽  
Stefanie Rinderle-Ma
Keyword(s):  
Clinical Data ◽  
Process Mining ◽  
Process Models ◽  
Time Constraints ◽  
Actual Process ◽  
Conformance Checking ◽  
Event Logs ◽  
Melanoma Surveillance ◽  
Medical University ◽  
Medical Guidelines

Background: Process mining is a relatively new discipline that helps to discover and analyze actual process executions based on log data. In this paper we apply conformance checking techniques to the process of surveillance of melanoma patients. This process consists of recurring events with time constraints between the events. Objectives: The goal of this work is to show how existing clinical data collected during melanoma surveillance can be prepared and pre-processed to be reused for process mining. Methods: We describe an approach based on time boxing to create process models from medical guidelines and the corresponding event logs from clinical data of patient visits. Results: Event logs were extracted for 1023 patients starting melanoma surveillance at the Department of Dermatology at the Medical University of Vienna between January 2010 and June 2017. Conformance checking techniques available in the ProM framework and explorative applied process mining techniques were applied. Conclusions: The presented time boxing enables the direct use of existing process mining frameworks like ProM to perform process-oriented analysis also with respect to time constraints between events.

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