Configurable Process Mining: Variability Discovery Approach

Sikal, Rabab; Sbai, Hanae; Kjiri, Laïla

doi:10.1109/cist.2018.8596526

Cited by 12 publications

(10 citation statements)

References 8 publications

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“…The comparative studies presented in these two works showed the lack of support for variability discovery for various process perspectives. This paper extends the work originally presented in the 2018 IEEE 5th International Congress on Information Science and Technology (CiSt) [11] that we complete by proposing an approach for configurable process model creation directly from event logs. The organization of this paper is as follows: section 2 defines the background of our research field, while section 3 reviews approaches working on configurable process model discovery.…”

Section: Introductionmentioning

confidence: 67%

“…The contribution presented in [11] proposes a variability discovery approach for business processes taking into account the variability of resource perspective. In this paper, we shed light on our framework and its components.…”

Section: Framework Architecturementioning

confidence: 99%

“…The discovery approach comes after, to create the configurable process model directly from event logs without using merging techniques. Figure 4: Architecture of the proposed framework [11] The figure 4 presents the four components of the proposed framework:…”

Section: Framework Architecturementioning

confidence: 99%

“…It uses two algorithms to discover variability elements in detail. The first discovers the variability of activities [11] and the second discovers the variability of resources [23]. As output, the module generates i) a variability specification file, with variation points, variants, and variation point types for both activity and resource.…”

Section: Framework Architecturementioning

confidence: 99%

“…Moreover, existing approaches for configurable model creation use algorithms to construct configurable model by merging similar variant models, which result in large and complex models. In the light of these limitations, we have proposed in [11,12] a multi-perspective configurable process discovery approach with respect to variability of activities and resources. The comparative studies presented in these two works showed the lack of support for variability discovery for various process perspectives.…”

Section: Introductionmentioning

confidence: 99%

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Configurable Process Model: Discovery Approach from Event Logs

Sikal¹,

Sbai²,

Kjiri³

2020

Adv. sci. technol. eng. syst. j.

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In the domain of business process management, the configurable process model is widely used to optimize time and cost of business process models design, which is known as the concept of "reuse". Using process mining techniques for process model discovery helps to provide a better view on processes and improve quality of models. The majority of existing configurable model discovery approaches work intensively on control flow discovery as main process perspective without considering other perspectives such as resources and data, and do not propose a detailed discovery of variability elements. In addition, the configurable process model creation is generally done by merging variant models not directly from event logs, which is not the optimal way to get a reliable configurable process model. This paper presents an overview of new multi-perspective variability discovery approach. The approach respects the variability of different process perspectives and allows users to create a configurable process model directly from event logs.

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Section: Introductionmentioning

confidence: 67%

Section: Framework Architecturementioning

confidence: 99%

Section: Framework Architecturementioning

confidence: 99%

Section: Framework Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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