Process Logo: An Approach for Control-Flow Visualization of Information System Process in Process Mining
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
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.
Description
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
