Samenvatting
Conformance checking enables organizations to automatically identify compliance violations based on the analysis of observed event data. A crucial requirement for conformance-checking techniques is that observed events can be mapped to normative process models used to specify allowed behavior. Without a mapping, it is not possible to determine if an observed event trace conforms to the specification or not. A considerable problem in this regard is that establishing a mapping between events and process model activities is an inherently uncertain task. Since the use of a particular mapping directly influences the conformance of an event trace to a specification, this uncertainty represents a major issue for conformance checking. To overcome this issue, we introduce a probabilistic conformance-checking technique that can deal with uncertain mappings. Our technique avoids the need to select a single mapping by taking the entire spectrum of possible mappings into account. A quantitative evaluation demonstrates that our technique can be applied on a considerable number of real-world processes where existing conformance-checking techniques fail.
Originele taal-2 | Engels |
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Artikelnummer | 8634941 |
Pagina's (van-tot) | 927-940 |
Aantal pagina's | 14 |
Tijdschrift | IEEE Transactions on Knowledge and Data Engineering |
Volume | 32 |
Nummer van het tijdschrift | 5 |
DOI's | |
Status | Gepubliceerd - 1 mei 2020 |
Financiering
Han van der Aa is funded by a postdoctoral grant from the Alexander von Humboldt Foundation.