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Overcoming individual process model matcher weaknesses using ensemble matching

机译:使用集成匹配克服单个过程模型匹配器的弱点

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In recent years, a considerable number of process model matching techniques have been proposed. The goal of these techniques is to identify correspondences between the activities of two process models. However, the results from the Process Model Matching Contest 2015 reveal that there is still no universally applicable matching technique and that each technique has particular strengths and weaknesses. It is hard or even impossible to choose the best technique for a given matching problem. We propose to cope with this problem by running an ensemble of matching techniques and automatically selecting a subset of the generated correspondences. To this end, we propose a Markov Logic based optimization approach that automatically selects the best correspondences. The approach builds on an adaption of a voting technique from the domain of schema matching and combines it with process model specific constraints. Our experiments show that our approach is capable of generating results that are significantly better than alternative approaches. (C) 2017 Elsevier B.V. All rights reserved.
机译:近年来,已经提出了大量的过程模型匹配技术。这些技术的目标是识别两个过程模型的活动之间的对应关系。但是,2015年过程模型匹配竞赛的结果表明,仍然没有普遍适用的匹配技术,并且每种技术都有其特定的优点和缺点。对于给定的匹配问题,很难甚至不可能选择最佳技术。我们建议通过运行一组匹配技术并自动选择生成的对应项的子集来解决此问题。为此,我们提出了一种基于马尔可夫逻辑的优化方法,该方法可自动选择最佳对应关系。该方法基于对模式匹配领域的投票技术的改编,并将其与特定于流程模型的约束相结合。我们的实验表明,我们的方法能够产生比替代方法更好的结果。 (C)2017 Elsevier B.V.保留所有权利。

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