Towards Multi-perspective conformance checking with fuzzy sets

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Abstract

A crucial issue for today’s organizations is to ensure that the executions of their processes comply with a set of constraints like, e.g., internal managerial choices or external legal requirements.Conformance checking techniques are widely adopted to monitor the execution of the organization processes and pinpoint possible discrepancies with respect to the prescribed behaviors. However, state of the art approaches adopt a crisp evaluation of deviations, with the result that small violations are considered at the same level of significant ones. This affects the quality of the provided diagnostics, especially when there exists some tolerance with respect to reasonably small violations, and hampers the flexibility of the process. In this work, we propose a novel approach which allows to represent actors’tolerance with respect to violations and to account for severity of deviations when assessing executions compliance. Besides improving the quality of the provided diagnostics, allowing some tolerance in deviation assessment also enhances the flexibility of conformance checking techniques and, indirectly, paves the way for improving the resilience of the overall process management system.
Original languageEnglish
Title of host publicationWorkshop on Data Fusion for Artificial Intelligence (DAFUSAI 2020)
Subtitle of host publication24th European Conference on Artificial Intelligence Workshops
Publication statusPublished - 2020
EventWorkshop on Data Fusion for Artificial Intelligence DAFUSAI: 24th European Conference on Artificial Intelligence -
Duration: 29 Aug 20208 Sep 2020

Workshop

WorkshopWorkshop on Data Fusion for Artificial Intelligence DAFUSAI
Period29/08/208/09/20

Bibliographical note

Technical Contribution 4

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