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首页> 外文期刊>International journal of web services research >Development of Distance Measures for Process Mining, Discovery, and Integration
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Development of Distance Measures for Process Mining, Discovery, and Integration

机译：开发用于过程挖掘，发现和集成的距离度量

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Business processes continue to play an important role in today's service-oriented enterprise computing systems. Mining, discovering, and integrating process-oriented services has attracted growing attention in the recent years. In this article, we present a quantitative approach to modeling and capturing the similarity and dissimilarity between different process designs. We derive the similarity measures by analyzing the process dependency graphs of the participating workflow processes. We first convert each process dependency graph into a normalized process matrix. Then we calculate the metric space distance between the normalized matrices. This distance measure can be used as a quantitative and qualitative tool in process mining, process merging, and process clustering, and ultimately it can reduce or minimize the costs involved in design, analysis, and evolution of workflow systems.
机译：业务流程在当今面向服务的企业计算系统中继续发挥重要作用。近年来，面向过程的服务的挖掘，发现和集成已引起越来越多的关注。在本文中，我们提出了一种定量方法，用于建模和捕获不同过程设计之间的相似性和不相似性。我们通过分析参与的工作流程过程的过程依赖图来得出相似性度量。我们首先将每个过程依赖图转换为规范化的过程矩阵。然后，我们计算归一化矩阵之间的度量空间距离。此距离度量可以用作过程挖掘，过程合并和过程集群中的定量和定性工具，最终可以减少或最小化工作流系统的设计，分析和演进所涉及的成本。

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