Workflow mining: A survey of issues and approaches

Aalst, Wil M. P. van der; Dongen, Boudewijn F. van; Herbst, Joachim; Măruşter, Laura; Schimm, Guido; Weijters, A. J. M. M.

doi:10.1016/s0169-023x(03)00066-1

Cited by 834 publications

(480 citation statements)

References 26 publications

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“…Process mining [23] describes a family of a posteriori analysis techniques exploiting the information recorded in traces of actions. This process information can be used to discover the underlying process schema, when no a priori model is available.…”

Section: Discussionmentioning

confidence: 99%

A Case-Based Approach to Business Process Monitoring

Montani

Leonardi

2010

Artificial Intelligence in Theory and Practice III

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Abstract. The agile workflow technology deals with flexible workflow adaptation and overriding, in case of foreseen as well as unforeseen changes and problems in the operating business environment. One key issue that an agile workflow system should address is Business Process (BP) monitoring. This consists in properly highlighting and organizing non-compliances and adaptations with respect to the default process schema. Such an activity can be the starting point for other very critical tasks, such as quality assessment and process reengineering.In this paper, we introduce an automated support to BP monitoring, which exploits the Case-based Reasoning (CBR) methodology. CBR is particularly well suited for managing exceptional situations, and has been proposed in the literature for process change reuse and workflow adaptation support. Our work extends these functionalities by retrieving traces of process execution similar to the current one, which can then be automatically clustered. Retrieval and clustering results can provide support both to end users, in the process instance execution phase, and to process engineers, in (formal) process quality evaluation and long term process schema redefinition. Our approach in practice is illustrated by means of a case study in the field of stroke management.

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Section: Discussionmentioning

confidence: 99%

A Case-Based Approach to Business Process Monitoring

Montani

Leonardi

2010

Artificial Intelligence in Theory and Practice III

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“…The MXML data format [2] and the Extensible Event Stream (XES) standard 3 used by ProM and Aris are, as for the Aperture model, general purpose, flexible and extensible business process representations.…”

Section: Related Workmentioning

confidence: 99%

“…-by automatically extracting process models from existing systems logs, event logs, database transactions, audit trail events or other sources of information [1,2]; -by allowing instant analysis of the business processes using interactive visual displays of the process workflow; -by identifying specific case characteristics or trends that influence processing times [3].…”

Section: Introductionmentioning

confidence: 99%

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A Lightweight RDF Data Model for Business Process Analysis

Leida

Majeed

Colombo

et al. 2013

Lecture Notes in Business Information Processing

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Abstract. This article presents a lightweight data representation model designed to support real time monitoring of business processes. The model is based on a shared vocabulary defined using open standard representations (RDF) allowing independence and extremely flexible interoperability between applications. The main benefit of this representation is that it is transparent to the data creation and analysis processes; furthermore it can be extended progressively when new information is available. Business Process data represented with this data model can be easily published on-line and shared between applications. After the definition of the data model, in this article, we demonstrate that with the use of this representation it is possible to retrieve and make use of domain specific information without any previous knowledge of the process. This model is a novel approach to real-time process data representation and paves the road to a complete new breed of applications for business process analysis.

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“…Process mining can be seen to contribute to this. It aims at extracting information IIP 2006 from event logs to capture the business process as it is being executed [15]. Process management is primarily concerned with the integration of task and context knowledge in application.…”

Section: Introductionmentioning

confidence: 99%

Development of an OLAP-Fuzzy Based Process Mining System for Quality Improvement

Ho¹,

Lau²

IFIP International Federation for Information Processing

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Abstract:Currently, companies active in the development of high-tech products has become more and more complex in the age of mass customization. Not only do they have to focus on improving product quality, but rather on gaining experience to modify the current processes in order to streamline the integrated workflow. A real-time process mining system (R-PMS) is developed to analyze the proposed XML based process data for discovering the hid-den relationship between processes. The new feature of this system is the in-corporation of the process mining engine, which is characterized by the combined capabilities of the Online Analytical Processing (OLAP) and fuzzy logic (FL), to form a robust framework for highlighting the undesirable process set-ting and parameters for further improvement in a real-time manner. The simulation results indicate that the OLAP based fuzzy approach is generally superior to those of conventional methods which offer higher flexibility on production process management with decision support ability, in this paper, the de-tailed architecture and a case study are included to demonstrate the feasibility of the proposed system.

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Workflow mining: A survey of issues and approaches

Cited by 834 publications

References 26 publications

A Case-Based Approach to Business Process Monitoring

A Case-Based Approach to Business Process Monitoring

A Lightweight RDF Data Model for Business Process Analysis

Development of an OLAP-Fuzzy Based Process Mining System for Quality Improvement

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