Process mining is a family of techniques that aim at analyzing businessprocess execution data recorded in event logs. Conformance checking is a branchof this discipline embracing approaches for verifying whether the behavior of aprocess, as recorded in a log, is in line with some expected behaviors providedin the form of a process model. The majority of these approaches require theinput process model to be procedural (e.g., a Petri net). However, in turbulentenvironments, characterized by high variability, the process behavior is lessstable and predictable. In these environments, procedural process models areless suitable to describe a business process. Declarative specifications,working in an open world assumption, allow the modeler to express severalpossible execution paths as a compact set of constraints. Any process executionthat does not contradict these constraints is allowed. One of the openchallenges in the context of conformance checking with declarative models isthe capability of supporting multi-perspective specifications. In this paper,we close this gap by providing a framework for conformance checking based onMP-Declare, a multi-perspective version of the declarative process modelinglanguage Declare. The approach has been implemented in the process mining toolProM and has been experimented in three real life case studies.
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