Federated Conformance Checking

• URL: http://arxiv.org/abs/2501.13576v1
• Date: Thu, 23 Jan 2025 11:30:13 GMT
• Title: Federated Conformance Checking
• Authors: Majid Rafiei, Mahsa Pourbafrani, Wil M. P. van der Aalst,
• Abstract summary: Conformance checking is a crucial aspect of process mining, where the main objective is to compare the execution of a process. We propose a privacy-aware federated conformance-checking approach that allows for evaluating the correctness of overall cross-organizational process models.
• Score: 0.1433758865948252
• License:
• Abstract: Conformance checking is a crucial aspect of process mining, where the main objective is to compare the actual execution of a process, as recorded in an event log, with a reference process model, e.g., in the form of a Petri net or a BPMN. Conformance checking enables identifying deviations, anomalies, or non-compliance instances. It offers different perspectives on problems in processes, bottlenecks, or process instances that are not compliant with the model. Performing conformance checking in federated (inter-organizational) settings allows organizations to gain insights into the overall process execution and to identify compliance issues across organizational boundaries, which facilitates process improvement efforts among collaborating entities. In this paper, we propose a privacy-aware federated conformance-checking approach that allows for evaluating the correctness of overall cross-organizational process models, identifying miscommunications, and quantifying their costs. For evaluation, we design and simulate a supply chain process with three organizations engaged in purchase-to-pay, order-to-cash, and shipment processes. We generate synthetic event logs for each organization as well as the complete process, and we apply our approach to identify and evaluate the cost of pre-injected miscommunications.

Related papers

• Mining Constraints from Reference Process Models for Detecting Best-Practice Violations in Event Log [1.389948527681755]
  We propose a framework for mining declarative best-practice constraints from a reference model collection. We demonstrate the capability of our framework to detect best-practice violations through an evaluation based on real-world process model collections and event logs.
  arXiv  Detail & Related papers  (2024-07-02T15:05:37Z)
• Extracting Process-Aware Decision Models from Object-Centric Process Data [54.04724730771216]
  This paper proposes the first object-centric decision-mining algorithm called Integrated Object-centric Decision Discovery Algorithm (IODDA) IODDA is able to discover how a decision is structured as well as how a decision is made.
  arXiv  Detail & Related papers  (2024-01-26T13:27:35Z)
• Object-Centric Conformance Alignments with Synchronization (Extended Version) [57.76661079749309]
  We present a new formalism that combines the ability of object-centric Petri nets to capture one-to-many relations and the one of Petri nets with identifiers to compare and synchronize objects based on their identity. We propose a conformance checking approach for such nets based on an encoding in satisfiability modulo theories (SMT)
  arXiv  Detail & Related papers  (2023-12-13T21:53:32Z)
• Relational Action Bases: Formalization, Effective Safety Verification, and Invariants (Extended Version) [67.99023219822564]
  We introduce the general framework of relational action bases (RABs) RABs generalize existing models by lifting both restrictions. We demonstrate the effectiveness of this approach on a benchmark of data-aware business processes.
  arXiv  Detail & Related papers  (2022-08-12T17:03:50Z)
• Conformance Checking with Uncertainty via SMT (Extended Version) [66.58864135810981]
  We show how to solve the problem of checking conformance of uncertain logs against data-aware reference processes. Our approach is modular, in that it homogeneously accommodates for different types of uncertainty. We show the correctness of our approach and witness feasibility through a proof-of-concept implementation.
  arXiv  Detail & Related papers  (2022-06-15T11:39:45Z)
• Extending Process Discovery with Model Complexity Optimization and Cyclic States Identification: Application to Healthcare Processes [62.997667081978825]
  The paper presents an approach to process mining providing semi-automatic support to model optimization. A model simplification approach is proposed, which essentially abstracts the raw model at the desired granularity. We aim to demonstrate the capabilities of the technological solution using three datasets from different applications in the healthcare domain.
  arXiv  Detail & Related papers  (2022-06-10T16:20:59Z)
• Predictive Compliance Monitoring in Process-Aware Information Systems: State of the Art, Functionalities, Research Directions [0.0]
  Business process compliance is a key area of business process management. Process compliance can be checked during process design time based on verification of process models. For existing compliance monitoring approaches it remains unclear whether and how compliance violations can be predicted.
  arXiv  Detail & Related papers  (2022-05-10T13:38:56Z)
• Trustworthy Artificial Intelligence and Process Mining: Challenges and Opportunities [0.8602553195689513]
  We show that process mining can provide a useful framework for gaining fact-based visibility to AI compliance process execution. We provide for an automated approach to analyze, remediate and monitor uncertainty in AI regulatory compliance processes.
  arXiv  Detail & Related papers  (2021-10-06T12:50:47Z)
• CoCoMoT: Conformance Checking of Multi-Perspective Processes via SMT (Extended Version) [62.96267257163426]
  We introduce the CoCoMoT (Computing Conformance Modulo Theories) framework. First, we show how SAT-based encodings studied in the pure control-flow setting can be lifted to our data-aware case. Second, we introduce a novel preprocessing technique based on a notion of property-preserving clustering.
  arXiv  Detail & Related papers  (2021-03-18T20:22:50Z)
• Partial Order Resolution of Event Logs for Process Conformance Checking [10.58705988536919]
  A key assumption of existing conformance checking techniques is that all events are associated with timestamps that allow to infer a total order of events per process instance. We present several estimators for this task, incorporating different notions of behavioral abstraction. Our experiments with real-world and synthetic data reveal that our approach improves accuracy over the state-of-the-art considerably.
  arXiv  Detail & Related papers  (2020-07-05T18:43:57Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.