Entropia: A Family of Entropy-Based Conformance Checking Measures for Process Mining
This provides a tool for process mining practitioners to evaluate model quality, but it appears incremental as it builds on existing entropy concepts.
The paper introduces Entropia, a command-line tool implementing entropy-based measures for conformance checking in process mining, which quantify precision and recall of process models discovered from event logs, offering useful properties and often fast computation.
This paper presents a command-line tool, called Entropia, that implements a family of conformance checking measures for process mining founded on the notion of entropy from information theory. The measures allow quantifying classical non-deterministic and stochastic precision and recall quality criteria for process models automatically discovered from traces executed by IT-systems and recorded in their event logs. A process model has "good" precision with respect to the log it was discovered from if it does not encode many traces that are not part of the log, and has "good" recall if it encodes most of the traces from the log. By definition, the measures possess useful properties and can often be computed quickly.