Conformance Checking Based on Uncertain Event-Activity Mappings

Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 323)


Conformance-checking techniques enable organizations to automatically determine whether business processes are executed according to their specifications. Particularly, they check if observed behavior, as recorded in an IT system and represented in the form of event logs, conforms to the allowed process behavior, typically captured in a process model [20]. The importance of conformance checking has been recognized in various contexts, such as legal compliance [229] and auditing [17]. Due to this importance, numerous conformance-checking techniques have been developed (cf. [12, 20, 191]). A crucial requirement for all these techniques is that the events contained in an event log can be related to the activities of a process model [11]. Without knowing the relations between events and model activities, it is not possible to determine if the behavior within a trace conforms to the behavior specified by a process model. Despite this dependence on the existence of a, so-called, event-to-activity mapping, establishing these mappings is a highly complex task. In particular, mapping techniques face considerable challenges caused by, among others, cryptic event names, non-conforming behavior, and noise [33]. As a result, the goal of mapping techniques is to choose the best mapping from a number of potential ones [167]. This introduces the risk that the selected mapping does not correctly capture the relations between traces and a process model. In the context of conformance checking, selecting an incorrect mapping is particularly harmful. If the selected mapping is incorrect, the results obtained through conformance checking can become incorrect as well. To overcome this issue, this chapter presents a conformance-checking technique that can be applied in spite of an uncertain mapping of events onto activities. Our technique assesses the conformance of a trace by considering the entire spectrum of potential mappings, rather than focusing on a single one. As a result, our conformance-checking technique avoids the risks associated with the selection of an incorrect mapping.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Humboldt University of BerlinBerlinGermany

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