Configuring Process Variants Through Semantic Reasoning in Systems Engineering

Detro, Silvana Pereira; Portela, Edoardo; Rocha, Eduardo Loures; Panetto, Hervé; Lezoche, Mario

doi:10.1002/inst.12179

Cited by 3 publications

(3 citation statements)

References 22 publications

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“…The authors extract knowledge from event logs to define ontologies, then combine them in semantic reasoning based on training samples. The added value over existing studies (Detro et al, 2017;De Toledo et al, 2019) is the application in self-defined BP context, respecting its different properties, such as: variability, unique paths, different ontologies, etc.…”

Section: Results Analysismentioning

confidence: 99%

“…Consequently, the self-defined BP ontologies, guidelines and process variants attributes are emerged. In this context, the use of semantic reasoning (Detro et al, 2017) is required, to recommend the suitable process that the user must be achieved, based on the engine knowledge, and learned from the user's objective and requirements.…”

Section: Managing Variabilitymentioning

confidence: 99%

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Mining Self-Defined Business Process in Electronic Administration

Lamghari

Saidi

Radgui

et al. 2022

International Journal of E-Services and Mobile Applications

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The information retrieval system is a set of resources and tools that allow users to search for information in a given domain. This system permits users to perform their research according to their objectives in diverse ways producing different behaviors. Even users with the same objective may follow different paths and stand different sub-processes, which are introduced as self-defined Business Processes that vary in terms of structure, objective, and result. This puts forward the difficulty of obtaining and studying these user’s behaviors. This paper targets the problem of representing and managing self-defined business process variability. A special interest is given to the use of process mining to deal with this challenge. In this regard, a case study about citizens in interaction with the Electronic Administration is presented, to discover and manage variability of this process type. The main result is a set of recommendations to end users.

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Section: Results Analysismentioning

confidence: 99%

Section: Managing Variabilitymentioning

confidence: 99%

Mining Self-Defined Business Process in Electronic Administration

Lamghari

Saidi

Radgui

et al. 2022

International Journal of E-Services and Mobile Applications

View full text Add to dashboard Cite

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“…In this context, two main definitions can be acquired (Van der Aalst et. al., 2009;Detro et. al., 2017;La rosa et al, 2017):…”

Section: B Variabilitymentioning

confidence: 99%

Unstructured Business Processes Improvement using Process Mining Techniques

Lamghari¹

2022

ASMScJ

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Executing loosely structured processes generate unstructured behaviours. Thus, an Unstructured Business Process (UBP) still has more issues that are difficult to be analysed and to be understood due to its complexity and variability. Moreover, the need of an instantiate response is clearly appeared in operational systems. Therefore, it is required to study related challenges that can be acquired during the transition from the structured BP to the unstructured one. In this context, process mining plays a dominant role to understand business process complexity using event data resulted from business process execution. Mainly, this paper treats three challenges related to unstructured BPs. The first challenge is how to support UBPs at runtime using process mining techniques. The second challenge is how to manage UBP variability taking into consideration variant conditions. The third challenge is how to adapt dynamically UBPs according to the company business rules and conditions.

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