Federated conformance checking

IF 3 2区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Majid Rafiei, Mahsa Pourbafrani, Wil M.P. van der Aalst
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引用次数: 0

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.
联邦一致性检查
一致性检查是流程挖掘的一个关键方面,其主要目标是将记录在事件日志中的流程的实际执行与参考流程模型(例如,以Petri网或BPMN的形式)进行比较。一致性检查能够识别偏差、异常或不符合实例。它为流程、瓶颈或与模型不兼容的流程实例中的问题提供了不同的视角。在联合(组织间)设置中执行一致性检查允许组织获得对整个过程执行的洞察,并识别跨组织边界的遵从性问题,从而促进协作实体之间的过程改进工作。在本文中,我们提出了一种具有隐私意识的联合一致性检查方法,该方法允许评估整个跨组织流程模型的正确性,识别错误沟通并量化其成本。为了进行评估,我们设计并模拟了一个供应链流程,其中有三个组织参与了从购买到付款、订单到现金和发货流程。我们为每个组织和整个过程生成综合事件日志,并应用我们的方法来识别和评估预注入错误沟通的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Information Systems
Information Systems 工程技术-计算机:信息系统
CiteScore
9.40
自引率
2.70%
发文量
112
审稿时长
53 days
期刊介绍: Information systems are the software and hardware systems that support data-intensive applications. The journal Information Systems publishes articles concerning the design and implementation of languages, data models, process models, algorithms, software and hardware for information systems. Subject areas include data management issues as presented in the principal international database conferences (e.g., ACM SIGMOD/PODS, VLDB, ICDE and ICDT/EDBT) as well as data-related issues from the fields of data mining/machine learning, information retrieval coordinated with structured data, internet and cloud data management, business process management, web semantics, visual and audio information systems, scientific computing, and data science. Implementation papers having to do with massively parallel data management, fault tolerance in practice, and special purpose hardware for data-intensive systems are also welcome. Manuscripts from application domains, such as urban informatics, social and natural science, and Internet of Things, are also welcome. All papers should highlight innovative solutions to data management problems such as new data models, performance enhancements, and show how those innovations contribute to the goals of the application.
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