Process Logo: An Approach for Control-Flow Visualization of Information System Process in Process Mining

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Date

2022

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Springer Science and Business Media Deutschland GmbH

Abstract

This paper proposes a new technique named “Process Logo†for visualizing the causal relationship between the activities of a process (Control flow). Traditional process mining algorithms rely on representing the activity as a sequence of operations modeled using nodes and edges, as the number of activities increases, the representation of the entire control flow becomes quite tedious. Process logo is a compact yet highly informative method for visually representing the process model. It visually summarizes the number of activities, sequence of execution, relative significance, and dependency between activities. It uses a dynamic programming method—sequence alignment and clustering approach with Levenshtein measure as a distance measure. The proposed method is evaluated on the synthetic event log, the experimental result is promising. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Keywords

Affinity propagation method, Dynamic programming, Entropy, Event logs, Information score, Levenshtein distance, Process discovery, Process mining, Process model, Progressive methods

Citation

Lecture Notes in Electrical Engineering, 2022, Vol.789, , p. 481-492

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