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Conference Papers Year : 2023

A Context-Based Approach for Real-Time Adaptation Need Detection

Abstract

The increasingly dynamic and changing environment in which business processes are evolving requires companies to adapt them frequently. Thus, we propose in this paper a new context-based approach recommending to analyze well the environmental changes. This approach recommends to structure knowledge required for process adaptation need in accordance with our BPMN4V-Context meta-model, which supports the modeling of the operating environment, using the context along with the versions of the model of each BPMN process and their use conditions. It also advocates (i) a filtering activity to retain only significant context changes in the monitored data, as low-level context parameters, (ii) a reasoning activity to deduce high-level context parameters from filtered low-level ones, enhancing the current situation of running processes and (iii) examining the current situation before its analysis in order to resolve problems related to the used units and synonym values. Finally, the feasibilit y and applicability of this approach is demonstrated by a case study from the crisis domain and two performance tests.

Dates and versions

hal-04252000 , version 1 (20-10-2023)

Identifiers

Cite

Jamila Oukharijane, Imen Ben Saïd, Mohamed Chaâbane, Éric Andonoff, Rafik Bouaziz. A Context-Based Approach for Real-Time Adaptation Need Detection. 20th International Conference on Smart Business Technologies (ICSBT 2023), Institute for Systems and Technologies of Information, Control and Communication (INSTICC), Jul 2023, Rome, Italy. pp.114--125, ⟨10.5220/0012148500003552⟩. ⟨hal-04252000⟩
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