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首页> 外文期刊>Journal of web semantics: >Evaluating and comparing ontology alignment systems: An MCDM approach
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Evaluating and comparing ontology alignment systems: An MCDM approach

机译：评估和比较本体对齐系统：MCDM方法

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Ontology alignment is vital in Semantic Web technologies with numerous applications in diverse disciplines. Due to diversity and abundance of ontology alignment systems, a proper evaluation can portray the evolution of ontology alignment and depicts the efficiency of a system for a particular domain. Evaluation can help system designers recognize the strength and shortcomings of their systems, and aid application developers to select a proper alignment system. This article presents a new evaluation and comparison methodology based on multiple performance metrics that accommodates experts' preferences via a multi-criteria decision-making (MCDM) method, i.e., Bayesian best-worst method (BWM). First, the importance of a performance metric for a specific task/application is determined according to experts' preferences. The alignment systems are then evaluated based on proposed expert-based collective performance (ECP) that takes into account multiple metrics as well as their calibrated importance. For comparison, the alignment systems are ranked based on a probabilistic scheme, where it includes the extent to which one alignment system is preferred over another. The proposed methodology is applied to six tracks from ontology alignment evaluation initiative (OAEI), where the importance of performance metrics are calibrated by designing a survey and eliciting the preferences of ontology alignment experts. Accordingly, the participating alignment systems in the OAEI 2018 are evaluated and ranked. While the proposed methodology is applied to six OAEI tracks to demonstrate its applicability, it can also be applied to any benchmark or application of ontology alignment. (C) 2020 The Author(s). Published by Elsevier B.V.
机译：本体对齐在具有多种学科的许多应用中的语义网络技术方面是至关重要的。由于本体对齐系统的多样性和丰富，适当的评估可以描绘本体对齐的演变，并描绘了特定领域的系统的效率。评估可以帮助系统设计师认识到其系统的实力和缺点，以及帮助应用程序开发人员选择适当的对齐系统。本文提出了一种基于多种性能度量的新评估和比较方法，该方法通过多标准决策（MCDM）方法，即贝叶斯最佳方法（BWM）来适应专家的偏好。首先，根据专家的偏好确定特定任务/应用程序的性能度量的重要性。然后基于所提出的基于专家的集体性能（ECP）来评估对准系统，该表现（ECP）考虑了多个度量，以及它们的校准重要性。为了比较，对准系统基于概率方案排序，其中包括一个对准系统优先于另一个对准系统的程度。该提出的方法应用于来自本体对准评估倡议（OAEI）的六条轨道，其中通过设计调查和引出本体对准专家的偏好来校准性能指标的重要性。因此，评估和排序OAEI 2018中的参与对准系统。虽然所提出的方法应用于六个OAEI轨道以证明其适用性，但它也可以应用于本体对齐的任何基准或应用。 （c）2020提交人。由elsevier b.v出版。

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