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Anti-Alignments -- Measuring The Precision of Process Models and Event Logs

Abstract : Processes are a crucial artefact in organizations, since they coordinate the execution of activities so that products and services are provided. The use of models to analyse the underlying processes is a well-known practice. However, due to the complexity and continuous evolution of their processes, organizations need an effective way of analysing the relation between processes and models. Conformance checking techniques asses the suitability of a process model in representing an underlying process, observed through a collection of real executions. One important metric in conformance checking is to asses the precision of the model with respect to the observed executions, i.e., characterize the ability of the model to produce behavior unrelated to the one observed. In this paper we present the notion of anti-alignment as a concept to help unveiling runs in the model that may deviate significantly from the observed behavior. Using anti-alignments, a new metric for precision is proposed. In contrast to existing metrics, anti-alignment based precision metrics satisfy most of the required axioms highlighted in a recent publication. Moreover, a complexity analysis of the problem of computing anti-alignments is provided, which sheds light into the practicability of using anti-alignment to estimate precision. Experiments are provided that witness the validity of the concepts introduced in this paper.
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https://hal.inria.fr/hal-02383546
Contributor : Thomas Chatain <>
Submitted on : Wednesday, November 27, 2019 - 6:11:37 PM
Last modification on : Saturday, May 1, 2021 - 3:46:23 AM

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  • HAL Id : hal-02383546, version 1
  • ARXIV : 1912.05907

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Thomas Chatain, Mathilde Boltenhagen, Josep Carmona. Anti-Alignments -- Measuring The Precision of Process Models and Event Logs. 2019. ⟨hal-02383546⟩

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