Measuring Similarity for Data-Aware Business Processes

Business process similarity measures are of vital importance for process repository management applications, such as process query, process recommendation, and process clustering. Most existing approaches measure process similarity by relying on control-flow structures only. This article investigates the role of data in process similarity measure. To incorporate data-flow information into business process control flow, it proposes a data-aware workflow net (DWF-net) by extending the classical workflow net with data reading and writing semantics. Then, we introduce three types of similarity measures, i.e., data item set-based similarity, data operation set-based similarity, and data-aware behavior-based similarity, to quantify the similarity of data-aware business processes from different perspectives. Next, a methodology is introduced to help process analysts apply these three measures in a systematical way. Finally, we evaluate the effectiveness and applicability of the proposed similarity measures by a group of comparative experiments. Note to Practitioners -Business process similarity measures play an increasingly important role in business process repository management. This work addresses the role of data for process similarity measures. To this end, three types of similarity measures, i.e., data item set-based similarity, data operation set-based similarity, and data-aware behavior-based similarity, are introduced to quantify the similarity of data-aware business processes from different perspectives. By comparative evaluation, the effectiveness and applicability are demonstrated. The proposed methodology is readily applicable to enterprise process repository management problems.