Aligning Business Process Models
Aligning Business Process Models
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DOI：
10.1109/edoc.2009.11
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发表时间：
2009-09
期刊：
影响因子：
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通讯作者：
R. Dijkman;M. Dumas;Luciano García-Bañuelos;R. Uba
中科院分区：
文献类型：
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作者：
R. Dijkman;M. Dumas;Luciano García-Bañuelos;R. Uba
本文研究了以下问题：给定一对业务流程模型，确定一个模型中的哪些元素与另一个模型中的哪些元素相关。此问题出现在合并业务流程模型的不同版本或变体的上下文中，或者在比较业务流程模型以显示它们的异同时出现。本文研究了两种解决这种对齐问题的方法：一种是纯粹基于元素对的词汇匹配，另一种是基于纠错图匹配。使用一组来自现实生活场景的模型，本文实证地表明，图匹配技术在获得类似召回率的同时，比单纯的词汇匹配技术产生了显著更高的准确率。
This paper studies the following problem: given a pair of business process models, determine which elements in one model are related to which elements in the other model. This problem arises in the context of merging different versions or variants of a business process model or when comparing business process models in order to display their similarities and differences. The paper investigates two approaches to this alignment problem: one based purely on lexical matching of pairs of elements and another based on error-correcting graph matching. Using a set of models taken from real-life scenarios, the paper empirically shows that graph matching techniques yield a significantly higher precision than pure lexical matching, while achieving comparable recall.