Similarity-Based Retrieval and Automatic Adaptation of Semantic Workflows

Bergmann, Ralph; Müller, Gilbert

doi:10.1007/978-3-319-64161-4_2

Cited by 12 publications

(9 citation statements)

References 37 publications

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“…By combining these methods, we expect a reduction of the computational and knowledge acquisition efforts that are often very high for planning-based approaches due to their use of comprehensive real world domain models (full observability assumption). Process-oriented Case-based Reasoning (POCBR) [4,17] is examined as an experience-based learning method that deals with the reuse of procedural experiential knowledge. We use the Camunda WfMS in combination with the Process-oriented Case-based Knowledge Engine (ProCAKE) [3], a system that is tailored for developing POCBR applications (cf.…”

Section: Experience-based Adaptation and Optimization Of Processesmentioning

confidence: 99%

Using Physical Factory Simulation Models for Business Process Management Research

Malburg

Seiger

Bergmann

et al. 2020

Business Process Management Workshops

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The production and manufacturing industries are currently transitioning towards more autonomous and intelligent production lines within the Fourth Industrial Revolution (Industry 4.0). Learning Factories as small scale physical models of real shop floors are realistic platforms to conduct research in the smart manufacturing area without depending on expensive real world production lines or completely simulated data. In this work, we propose to use learning factories for conducting research in the context of Business Process Management (BPM) and Internet of Things (IoT) as this combination promises to be mutually beneficial for both research areas. We introduce our physical Fischertechnik factory models simulating a complex production line and three exemplary use cases of combining BPM and IoT, namely the implementation of a BPM abstraction stack on top of a learning factory, the experiencebased adaptation and optimization of manufacturing processes, and the stream processing-based conformance checking of IoT-enabled processes.

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Section: Experience-based Adaptation and Optimization Of Processesmentioning

confidence: 99%

Using Physical Factory Simulation Models for Business Process Management Research

Malburg

Seiger

Bergmann

et al. 2020

Business Process Management Workshops

Self Cite

View full text Add to dashboard Cite

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“…Similarity measurement is a common task in workflow retrieval [16] and the related fields in data mining. A vast number of workflow representations have been designed for similarity measurement of workflows given about feature vectors [17].…”

Section: Related Workmentioning

confidence: 99%

Cross-domain graph based similarity measurement of workflows

Koohi-Var

Zahedi

2018

J Big Data

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“…Common features of workflows are important properties of workflows. They are effective in their potentially reusability [31]. We use similarity assessment of workflows to automate workflow improvement.…”

Section: Similarity Assessmentmentioning

confidence: 99%

“…after reconciling and improving a workflow, it can be reserved to reuse as a proposed sample solution for the same workflow, later. Important properties of workflows are effective in their potentially reusability [31]. We use similarity assessment of workflows to automate workflow improvement.…”

Section: Similarity Assessmentmentioning

confidence: 99%

Cross-domain similarity assessment for workflow improvement to handle Big Data challenge in workflow management

Koohi-Var

Zahedi

2018

J Big Data

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Ubiquitous computing is a concept in engineering where the computing is made to appear anytime and everywhere. This paradigm is also described as pervasive computing, or ambient intelligence. Considering ubiquitous computing perspectives can be useful to manage workflows, because running workflows usually needs large-scale computing resources and massive storages [1] and considering the relatedness between data. Ubicomp is a concept in engineering where the computing is made to appear anytime and everywhere. This paradigm is also described as pervasive computing, or ambient intelligence. Figure 1 represents Big Data challenges in workflow management systems (WfMSs). By creating workflows, skilled and non-skilled designers can manage and control their tasks. It is necessary to gather all the data and to consider various aspects of information in the design of a clear and helpful workflow, unless the workflow might cusses destructive effects on experiment or activities. Therefore, the WfMSs

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Similarity-Based Retrieval and Automatic Adaptation of Semantic Workflows

Cited by 12 publications

References 37 publications

Using Physical Factory Simulation Models for Business Process Management Research

Using Physical Factory Simulation Models for Business Process Management Research

Cross-domain graph based similarity measurement of workflows

Cross-domain similarity assessment for workflow improvement to handle Big Data challenge in workflow management

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