Comparative Analysis of Process Mining Algorithms in Python

Gomes, André Filipe Domingos; Lacerda, Ana Cristina Wanzeller Guedes de; Fialho, Joana

doi:10.1007/978-3-030-91421-9_3

Cited by 4 publications

(3 citation statements)

References 23 publications

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“…The predominance of healthcare datasets among those used for evaluation purposes demonstrates that the processes in the healthcare domain are more complex than any other domain. The patient treatment process in the healthcare industry consists of numerous activities and that too deals with various disciplines and subareas [11], [71], which creates inherent complexity. Similarly, the bank loan application process gets complex due to different process execution behaviors triggered by a range of customer types, loans, and financial statuses.…”

Section: Discussionmentioning

confidence: 99%

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Complex Process Modeling in Process Mining: A Systematic Review

et al. 2022

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Process mining techniques are used to extract knowledge about the efficiency and compliance of an organization's business processes through process models. Real-life processes are unstructured, and applying process mining to discover such processes often results in complex process models that do not provide actionable insights. Several solutions have been presented to overcome this problem. However, the process mining domain lacks an explicit definition of complexity and its measurement. This vagueness results in ad-hoc solutions that vary according to the approach, modelling construct, and process properties. Additionally, the strength and limitations of the proposed solutions have not been adequately highlighted. Therefore, we conducted a systematic literature review on complexity in process mining over six popular scholarly indexing databases. Based on the review results, an explicit definition of complexity, the main contributing factors and their impact on process mining results were identified. We discovered various process complexity matrices and their application context. The analysis of studies led to the development of a taxonomy consisting of four different approaches for addressing the complexity problem, along with their strengths and limitations. Finally, the open research challenges and potential for future research are discussed.

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Section: Discussionmentioning

confidence: 99%

“…This variable process is called a complex or unstructured process. The model generated by process mining using logs of such an environment results in a complex or spaghetti-like process model [8], [11]. Examples of complex and structured process models are shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Complex Process Modeling in Process Mining: A Systematic Review

et al. 2022

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“…There are mining tools that use specialized mining algorithms to identify patterns from event data recorded in information management systems (Rojas et al, 2019). The articles (Gomes et al, 2021b) and (Gomes et al, 2022) make a comparative analysis of some of the main available algorithms. Already in (Gomes et al, 2021a), a comparative analysis of tools is carried out and it is concluded that Disco is the most suitable to use, despite the need for a license in its most complete versions.…”

Section: Process Miningmentioning

confidence: 99%