  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.
