Adaptable Cross-organizational Unstructured Business Processes via Dynamic Rule-based Semantic Network

Ehsan Alirezaei () and Saeed Parsa ()
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Ehsan Alirezaei: Iran University of Science and Technology
Saeed Parsa: Iran University of Science and Technology

Information Systems Frontiers, 2020, vol. 22, issue 3, No 15, 787 pages

Abstract: Abstract Rapid online adaptation to the new business requirements can improve innovation level and market competency of collaborative organizations. Complex and unstructured processes are provision e-services in collaborative networks through web service inter-connections, which unanticipated changes made it hard to manage them. In a cross-organizational domain, when partners deal with unexpected changes, the received requests are represented as complex theories, and business process adaptation will be more complicated in the occurrence of concept drifts. Rapid prediction and adaptation to new situations need concept drift detection and novel class prediction mechanism for the overall collaborative network processes in both data and control flows. In this article, a new approach to the online reflection of distributed rule concept drifts of collaborative network reference processes is introduced. The solution to the data-informed adaptation of unstructured process employed managing rule concept drifts and cross-organizational processes restructuring via the distributed model with minor updates. The method could react to the new events via an ensemble prediction mechanism. Its architecture has major components for monitoring, dynamic distributed rule reconfiguration, and partners side components. The paper suggests a service-oriented semantic network of distributed rules for e-services provision, substitution, and replacement via management of choreographed web-services. The approach has been validated and verified with real data belonging to the healthcare domain. The results prove the adaptation mechanism efficiency of the daily changes.

Keywords: Unstructured processes; Business process adaptation; Collaborative network; Ensemble prediction; Choreographed web-services (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10796-018-9886-z

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