Provided by: Eindhoven University of Technology
Topic: Big Data
Date Added: Jul 2010
Process mining techniques attempt to extract non-trivial knowledge and interesting insights from event logs. Process models can be seen as the \"Maps\" describing the operational processes of organizations. Unfortunately, traditional process discovery algorithms have problems dealing with less-structured processes. Furthermore, existing discovery algorithms do not consider the analyst's context of analysis. As a result, the current models (i.e., \"Maps\") are difficult to comprehend or even misleading. To address this problem, the authors propose a two-phase approach based on common execution patterns.