History-based construction of log-process alignments for conformance checking : discovering what really went wrong

Alignments provide a robust approach for conformance checking which has been largely applied in various contexts such as auditing and performance analysis. Alignment-based conformance checking techniques pinpoint the deviations causing nonconformity based on a cost function. However, such a cost function is often manually defined on the basis of human judgment and thus error-prone, leading to alignments that do not provide the most probable explanations of nonconformity. This paper proposes an approach to automatically define the cost function based on information extracted from the past process executions. The cost function only relies on objective factors and thus enables the construction of the most probable alignments, i.e. alignments that provide the most probable explanations of nonconformity. Our approach has been implemented in ProM and assessed using both synthetic and real-life data. Keywords: Conformance checking, alignments, cost functions