Entropia: A Family of Entropy-Based Conformance Checking Measures for Process Mining

by   Artem Polyvyanyy, et al.

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 fast.



There are no comments yet.


page 1

page 2

page 3

page 4


An Entropic Relevance Measure for Stochastic Conformance Checking in Process Mining

Given an event log as a collection of recorded real-world process traces...

The Imprecisions of Precision Measures in Process Mining

In process mining, precision measures are used to quantify how much a pr...

Tracelets and Tracelet Analysis Of Compositional Rewriting Systems

Taking advantage of a recently discovered associativity property of rule...

Evaluating Conformance Measures in Process Mining using Conformance Propositions (Extended version)

Process mining sheds new light on the relationship between process model...

Temporal Conformance Checking at Runtime based on Time-infused Process Models

Conformance checking quantifies the deviations between a set of traces i...

Conformance Checking for a Medical Training Process Using Petri net Simulation and Sequence Alignment

Process Mining has recently gained popularity in healthcare due to its p...

Automated simulation and verification of process models discovered by process mining

This paper presents a novel approach for automated analysis of process m...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.