Towards Multi-perspective conformance checking with fuzzy sets
  Conformance checking techniques are widely adopted to pinpoint possible
discrepancies between process models and the execution of the process in
reality. However, state of the art approaches adopt a crisp evaluation of
deviations, with the result that small violations are considered at the same
level of significant ones. This affects the quality of the provided
diagnostics, especially when there exists some tolerance with respect to
reasonably small violations, and hampers the flexibility of the process. In
this work, we propose a novel approach which allows to represent actors'
tolerance with respect to violations and to account for severity of deviations
when assessing executions compliance. We argue that besides improving the
quality of the provided diagnostics, allowing some tolerance in deviations
assessment also enhances the flexibility of conformance checking techniques
and, indirectly, paves the way for improving the resilience of the overall
process management system.
