Ranking-Based Evaluation of Process Model Matching

DOI：

10.1007/978-3-319-69462-7_19

发表时间：

2017-10

期刊：

影响因子：

通讯作者：

中科院分区：

其他

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作者：

Elena Kuss;H. Leopold;Christian Meilicke;H. Stuckenschmidt

流程模型匹配是指自动检测两个流程模型之间语义等效或相似的活动。流程模型匹配器的输出是许多高级流程模型分析技术的基础，因此必须尽可能准确。然而，衡量流程模型匹配器的性能是一项艰巨的任务。一方面，很难定义哪些对应关系实际上是正确的。另一方面，适当考虑匹配器的输出具有挑战性，因为它们通常产生 0 到 1 之间的置信值。在本文中，我们提出了流程模型匹配器的第一个评估程序，以解决这两个挑战。核心思想是根据计算出的对应关系和所需对应关系的置信度值对它们进行排名，并使用斯皮尔曼排名相关系数对它们进行比较。我们进行了深入的评估，其中应用了新的评估程序，并说明了它如何帮助获得有趣的见解。

Process model matching refers to the automatic detection of semantically equivalent or similar activities between two process models. The output of process model matchers is the basis for many advanced process model analysis techniques and, therefore, must be as accurate as possible. Measuring the performance of process model matchers, however, is a difficult task. On the one hand, it is hard to define which correspondences are actually correct. On the other hand, it is challenging to appropriately take the output of matchers into account, because they often produce confidence values between zero and one. In this paper, we propose the first evaluation procedure for process model matchers that addresses both of these challenges. The core idea is to rank both the computed and the desired correspondences based on their confidence values and compare them using the Spearman’s rank correlation coefficient. We perform an in-depth evaluation in which we apply the new evaluation procedure and illustrate how it helps gaining interesting insights.

Ranking-Based Evaluation of Process Model Matching - (Short Paper)

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