Business process fitness analysis based on alignment processing and deviation detection

Due to the variability and dynamics of business processes in practical applications, the conformance between logs and given models needs to be checked and analyzed. The current conformance method aligns the log with the model directly to detect the overall deviation, while the deviation from the global observation will affect the accuracy of conformance checking. Therefore, a new method for analyzing conformance by searching for optimal alignment between logs and a given model was proposed. The selective subsequence reference activities was set to divide the type of alignment, and the minimum deviation alignment in the process of elimination was found through the arithmetic of alignment search. Then the optimal alignment was determined by analyzing the precision and behavior relations of the same deviation replay with different forms in the model sub-modules. The method was evaluated through case studies and comparative experiments of actual business process, and the results showed that accurate detection deviation could significantly improve the measurement value of fitness. By analyzing the detailed data of fitness measurement, the conclusion that narrowing the range of alignment comparison could reduce the calculated amount was obtained. © 2020, Editorial Department of CIMS. All right reserved.