Abstract
In this paper, within the framework of process mining we examine the Maximal Pattern Mining method introduced by Liesaputra et al. in [1]. This method constructs a transition graph, i.e. a labelled directed graph for traces with similar structure. The idea behind the algorithm is to analyze the traces in the event log, identify loops, parallel events and optionality between them, in order to determine the maximal patterns. In [1], the authors provide a pseudo code for the skeleton of their algorithm and discuss some parts, but other parts are not detailed. Here, we briefly discuss the steps of the algorithm and elaborate the steps that are not explained in [1]. We introduce some new subroutines to handle the loops, parallel and optional sequences.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
