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Title:
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FRAGMENTATION-DRIVEN SIMILARITY DETECTION IN LARGE BUSINESS PROCESS MODELS |
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Author(s):
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Wiem Kbaier, Asma Mejri and Sonia Ayachi Ghannouchi |
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ISBN:
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978-989-8704-62 |
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Editors:
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Paula Miranda and Pedro Isaías |
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Year:
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2024 |
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Edition:
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Single |
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Keywords:
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Large Business Process Models, Structural Similarity, Fragmentation, Reference Models |
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Type:
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Full |
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First Page:
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101 |
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Last Page:
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108 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Business process models are vital for organizations to analyse, understand, and optimize their operations. However, as
these processes grow in complexity, managing large-scale models becomes increasingly difficult. This paper introduces a
new method for decomposing large business process models into smaller fragments, enabling a detailed comparison with
a reference model. By applying structural similarity measurement using the Jaccard Index, the approach identifies the extent
of similarity between each fragment and the reference model. Our approach was applied using a running example, which
proved its effectiveness |
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