Anti-alignments—Measuring the precision of process models and event logs

Chatain, Thomas; Boltenhagen, Mathilde; Carmona, Josep

doi:10.1016/j.is.2020.101708

Cited by 10 publications

(9 citation statements)

References 19 publications

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“…hA, C, D, H, F, Ii} and two of its associated models specifically chosen for showing the impact of the heuristics: the generating model and the flower model. The models can be found in [5] page 4, [20] and [4] page 10.…”

Section: A Comparison Of the Results Obtained With The Different Heuristicsmentioning

confidence: 99%

“…The same year, the authors present in [5] how those conformance artefacts can be used for measuring precision but also generalization, i.e., two fundamental metrics still in elaboration in process mining [1]. Anti-alignments have been proposed for both the Hamming distance and the Levenshtein distance [4]. Nicely, anti-alignment based precision metrics satisfy the necessary axioms for a precision metric [10].…”

Section: Related Workmentioning

confidence: 99%

“…Definition 5 (Anti-Alignment based Precision). For an event log L and a model N , ✏-precision P ✏ aa (N, L) [4] is defined by:…”

Section: Common Distance Used In Process Mining Is a Version Of The Levenshtein Edit Distancementioning

confidence: 99%

“…Comparing a possibly infinite language (i.e., the process model may accept an infinite set of runs) with respect to a finite language (the event log is a finite set of traces) makes conformance checking techniques challenging. The notion of anti-alignment [3], [4], however, aims at aiding this comparison, since it explores the process model to find a run that deviates the most with respect to all the traces in the event log. Anti-alignments can be used for several purposes, e.g., evaluating the precision/generalization of a process model with respect to an event log [5], or log-based simulation of a process model.…”

Section: Introductionmentioning

confidence: 99%

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An A^*-Algorithm for Computing Discounted Anti-Alignments in Process Mining

Boltenhagen

Chatain

Carmona

2021

2021 3rd International Conference on Process Mining (ICPM)

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Process mining techniques aim at analyzing and monitoring processes through event data. Formal models like Petri nets serve as an effective representation of the processes. A central question in the field is to assess the conformance of a process model with respect to the real process executions. The notion of anti-alignment, which represents a model run that is as distant as possible to the process executions, has been demonstrated to be crucial to measure precision of models. However, the only known algorithm for computing anti-alignments has a high complexity, which prevents it from being applied on real-life problem instances. In this paper we propose a novel algorithm for computing anti-alignments, based on the well-known graphbased A ⇤ scheme. By introducing a discount factor in the edit distance used for the search of anti-alignments, we obtain the first efficient algorithm to approximate them. We show how this approximation is quite accurate in practice, by comparing it with the optimal results for small instances where the optimal algorithm can also compute anti-alignments. Finally, we compare the obtained precision metric with respect to the state-of-the-art metrics in the literature for real-life examples.

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Section: A Comparison Of the Results Obtained With The Different Heuristicsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…Definition 5 (Anti-Alignment based Precision). For an event log L and a model N , ✏-precision P ✏ aa (N, L) [4] is defined by:…”

Section: Common Distance Used In Process Mining Is a Version Of The Levenshtein Edit Distancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An A^*-Algorithm for Computing Discounted Anti-Alignments in Process Mining

Boltenhagen

Chatain

Carmona

2021

2021 3rd International Conference on Process Mining (ICPM)

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“…Overall, the current paper adopts SAT as a reasoning engine to compute conformance checking artefacts like alignments, multi-alignments and anti-alignments, over the edit distance. Furthermore, we show for the first time how the baseline encoding for Levenshtein edit distance, reported in recent works [7,11], can be significantly optimized to process larger instances. Formal proofs are provided of these optimizations, and a novel adaptation of the SAT objective function to improve the quality of the obtained artefacts is proposed in this paper.…”

Section: Introductionmentioning

confidence: 97%

Optimized SAT encoding of conformance checking artefacts

2020

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Conformance checking is a growing discipline that aims at assisting organizations in monitoring their processes. On its core, conformance checking relies on the computation of particular artefacts which enable reasoning on the relation between observed and modeled behavior. It is widely acknowledge that the computation of these artifacts is the lion's share of conformance checking techniques. This paper shows how important conformance artefacts like alignments, anti-alignments or multi-alignments, defined over the Levenshtein edit distance, can be efficiently computed by encoding the problem as an optimized SAT instance. From a general perspective, the work advocates for a unified family of techniques that can compute conformance artefacts in the same way. The implementation of the techniques presented in this paper show capabilities for dealing with both synthetic and real-life instances, which may open the door for a fresh way of applying conformance checking in the near future.

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Timed Alignments with Mixed Moves

Rino,

Chatain

2024

Lecture Notes in Business Information Processing

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Anti-alignments—Measuring the precision of process models and event logs

Cited by 10 publications

References 19 publications

An A^*-Algorithm for Computing Discounted Anti-Alignments in Process Mining

An A^*-Algorithm for Computing Discounted Anti-Alignments in Process Mining

Optimized SAT encoding of conformance checking artefacts

Timed Alignments with Mixed Moves

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Anti-alignments—Measuring the precision of process models and event logs

Cited by 10 publications

References 19 publications

An A*-Algorithm for Computing Discounted Anti-Alignments in Process Mining

An A*-Algorithm for Computing Discounted Anti-Alignments in Process Mining

Optimized SAT encoding of conformance checking artefacts

Timed Alignments with Mixed Moves

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Product

Resources

About

An A^*-Algorithm for Computing Discounted Anti-Alignments in Process Mining

An A^*-Algorithm for Computing Discounted Anti-Alignments in Process Mining