Manoj Kumar, M.V.Bs, B.S.Sneha, H.R.Thomas, L.Annappa, B.Vishnu Srinivasa Murthy, Y.V.S.2026-02-062022Lecture Notes in Electrical Engineering, 2022, Vol.789, , p. 481-49218761100https://doi.org/10.1007/978-981-16-1338-8_40https://idr.nitk.ac.in/handle/123456789/30072This 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.Affinity propagation methodDynamic programmingEntropyEvent logsInformation scoreLevenshtein distanceProcess discoveryProcess miningProcess modelProgressive methods