Authors: Hind R'bigui; Chiwoon Cho
Addresses: School of Industrial Engineering, University of Ulsan, Ulsan 680-749, South Korea ' School of Industrial Engineering, University of Ulsan, Ulsan 680-749, South Korea
Abstract: Business process mining is a new method that amalgamates business process modelling and analysis with data mining and machine learning techniques, whereby knowledge from event logs stored in today's information system is extracted to automatically construct business process models, identify bottlenecks, and improve the business processes. Since process mining has recently received attention among the research community, there are many challenges. The most important issues have been defined in the process mining manifesto. However, none of the published works investigated, or the defined challenges, have been solved and are still being encountered. Therefore, this paper provides a comprehensive and critical review of the literature in the context of process mining challenges. The contribution of this paper is to increase the maturity of the field of process mining by providing researchers with the state-of-the-art of the most important challenges of process mining.
Keywords: business process mining; process mining challenges; state-of-the-art; review; process mining manifesto; event data; event logs.
International Journal of Business Process Integration and Management, 2017 Vol.8 No.4, pp.285 - 303
Received: 22 Jul 2016
Accepted: 10 Aug 2017
Published online: 19 Dec 2017 *