A new Framework to improve Change Mining in Configurable Process
| Autor: | Mounia Fredj, Asmae Hmami, Hanae Sbai |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
business.industry
Business process Computer science Event (computing) Process (engineering) Process mining 02 engineering and technology Business process reengineering Change mining 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Software engineering business |
| Zdroj: | NISS |
| DOI: | 10.1145/3386723.3387853 |
| Popis: | The configurable process model is an important approach to reduce the redundancy involved in modeling, reengineering, and adapting a business process with its environment. While process mining approaches aim to discover and, verify conformance and enhance a process, connecting configurable processes and process mining shows considerable improvements, especially in terms of time and cost. However, the configurable process has rarely been applied in change mining. Our goal in this paper is to highlight the importance of using variability to improve change mining from a collection of event logs. We propose a framework that can detect and recommend changes, by mining changes from a collection of event logs. The main purpose is to allow engineers and business process designers to easily adjust business process with the environment changes. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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