A visual approach to spot statistically-significant differences in event logs based on process metrics
ConferentiebijdrageBolt Iriondo, A.J., De Leoni, M. & Van Der Aalst, W.M.P. (2016). A visual approach to spot statistically-significant differences in event logs based on process metrics. In P. Soffer, S. Nurcan, M. Bajec & J. Eder (Eds.), Advanced Information Systems Engineering (pp. 151-166). (Lecture Notes in Computer Science, No. 9694). Dordrecht: Springer. In Scopus Cited 7 times.
This paper addresses the problem of comparing different variants of the same process. We aim to detect relevant differences between processes based on what was recorded in event logs. We use transition systems to model behavior and to highlight differences. Transition systems are annotated with measurements, used to compare the behavior in the variants. The results are visualized as transitions systems, which are colored to pinpoint the significant differences. The approach has been implemented in ProM, and the implementation is publicly available. We validated our approach by performing experiments using real-life event data. The results show how our technique is able to detect relevant differences undetected by previous approaches while it avoids detecting insignificant differences.