Kwanghoon Pio Kim, Journal of Internet Computing and Services, Vol. 26, No. 1, pp. 65-77, Feb. 2025
10.7472/jksii.2025.26.1.65, Full Text:  HTML
Keywords: Business Process Models, information control nets, Process Management Systems, Process Intelligence, Process Event-Trace-Log Dataset, Process Log-Dataset Preprocessing, Process Mining, Process Pattern-Clustering Approaches

Abstract

This paper designs a core preprocessing framework for the log-data preprocessing module of a process mining system that supports the lifecycle management of business process models. Specifically, it proposes a process event-trace-log (ETL) pattern-clustering approach as a core preprocessing function within the functional module of a process mining system that discovers fundamental process patterns from process execution log data. Furthermore, the paper presents the development results of the process mining system incorporating the proposed pattern-clustering approach and verifies the experimental preprocessing effects. As a result, this paper designs and implements the process event-trace-log pattern-clustering approach as a key preprocessing algorithm of the ρ-algorithm, which is a representative structural information control net-based process mining algorithm, and verifies the accuracy of the proposed pattern-clustering approach.

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