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Title:
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ELOGQI: AN APPROACH FOR IMPROVING EVENT LOG QUALITY |
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Author(s):
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Khouloud Guizani and Sonia Ayachi Ghannouchi |
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ISBN:
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978-989-8704-71-9 |
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Editors:
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Paula Miranda and Pedro Isaías |
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Year:
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2025 |
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Edition:
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Single |
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Keywords:
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Business Process Modelling, Process-Mining Techniques, Data Quality, Log File Quality |
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Type:
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Full Paper |
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First Page:
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59 |
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Last Page:
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66 |
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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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Paper Abstract:
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For organizations that want to define and measure their progress toward their goals, evaluating process performance is an
ongoing challenge. We'll be looking at the quality of the data used in this process. Our goal is to specifically study process
performance by looking in-depth at the event log to get a valid result. This study looks at different issues that can appear
in an event log and proposes a meta-model to represent these issues and how they relate to the main concepts that make it
up. Our work focuses on the issues defined in our meta-model to propose plugins that detect and correct these issues.
Our proposed meta-model and the adopted plugins are an addition to existing related work. We defined each plugin using
pseudocode and a textual description. In this article, we validate the detection part through ProM plugins developed on
Eclipse. |
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