Passage challenges from data-intensive system to knowledge-intensive system related to process mining field

Lamghari, Zineb; Radgui, Maryam; Saidi, Rajaa; Rahmani, Moulay Driss

doi:10.1145/3333165.3333168

Cited by 3 publications

(3 citation statements)

References 33 publications

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“…Through this sub-section, we illustrate the still encountered issues related to process mining applied to UBPs. In this context, the main challenge is how to deal with the event logs complexity at runtime (Lamghari et al, 2019).…”

Section: A Complexitymentioning

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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Section: A Complexitymentioning

confidence: 99%

Unstructured Business Processes Improvement using Process Mining Techniques

Lamghari¹

2022

ASMScJ

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“…To do so, we demonstrate how workflows are passed between and through our UBP operational support approach work entities, respectively to the following order: (sub-section 5.1) preparing normative model in the management entity, (sub-section 5.2) detecting violations in the operational support entity, predicting and recommending events at runtime into construction and operational support entities (sub-sections 5.3 and 5.4). 2 https://data.4tu.nl/repository/uuid:270fd440-1057-4fb9-89a9-b699b47990f5…”

Section: Illustrative Examplementioning

confidence: 99%

“…Here, operational support approaches perform well with SBP, while they still a challenging task for UBP. In this respect, the [2,3,4,5,6] demonstrate the still encountered issues related to the UBP operational support application. This is justified by their unpredictability, flexibility, and complexity.…”

Section: Introductionmentioning

confidence: 99%

An operational support approach for Mining Unstructured Business Processes

Lamghari

Radgui

Saidi

et al. 2021

RITA

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The refined process mining framework contains a set of activities that use extracted information from event logs, discovered models and normative ones. Among these activities, we find those dealing with running events in a Structured Business Process (SBP) context, which are the Detect, the Predict and the Recommend activities. These three activities are nominated as an operational support system that aims at detecting deviations, predicting events and recommending actions. In this regard, operational support systems perform well on SBP while, it stills a challenging task for an Unstructured Business Process (UBP). This puts forward the difficulty of predicting events and recommending actions for UBP, because of its complex structure. In this context, simplification and structuring operations must be applied. Therefore, the intervention of other process mining activities is required for business process simplification and structuring. To this end, we present an operational support approach dealing with UBP, using the refined process mining framework activities.

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