02396nas a2200265   4500000000100000000000100001008004100002260001200043653002300055653002500078653002100103653001600124100001600140700001600156700001200172700001700184700001400201700001600215245006700231856008100298300001200379490000600391520171900397022001402116       2021                            d  c03/202110aBusiness Processes10aConformance Checking10aData Perspective10aFuzzy Logic1 aSicui Zhang1 aLaura Genga1 aHui Yan1 aHongchao Nie1 aXudong Lu1 aUzay Kaymak00aTowards Multi-perspective Conformance Checking with Fuzzy Sets  uhttps://www.ijimai.org/journal/sites/default/files/2021-02/ijimai_6_5_13.pdf  a134-1410 v63 aNowadays organizations often need to employ data-driven techniques to audit their business processes and ensure they comply with laws and internal/external regulations. Failing in complying with the expected process behavior can indeed pave the way to inefficiencies or, worse, to frauds or abuses. An increasingly popular approach to automatically assess the compliance of the executions of organization processes is represented by alignment-based conformance checking. These techniques are able to compare real process executions with models representing the expected behaviors, providing diagnostics able to pinpoint possible discrepancies. However, the diagnostics generated by state of the art techniques still suffer from some limitations. They perform a crisp evaluation of process compliance, marking process behavior either as compliant or deviant, without taking into account the severity of the identified deviation. This hampers the accuracy of the obtained diagnostics and can lead to misleading results, especially in contexts where there is some tolerance with respect to violations of the process guidelines. In the present work, we discuss the impact and the drawbacks of a crisp deviation assessment approach. Then, we propose a novel conformance checking approach aimed at representing actors’ tolerance with respect to process deviations, taking it into account when assessing the severity of the deviations. As a proof of concept, we performed a set of synthetic experiments to assess the approach. The obtained results point out the potential of the usage of a more flexible evaluation of process deviations, and its impact on the quality and the interpretation of the obtained diagnostics.  a1989-1660