Leveraging Horizontal Density Differences between Ontologies to Identify Missing Child Concepts: A Proof of Concept
Leveraging Horizontal Density Differences between Ontologies to Identify Missing Child Concepts: A Proof of Concept
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发表时间：
2018
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通讯作者：
V. Keloth;Zhe He;Yan Chen;J. Geller
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作者：
V. Keloth;Zhe He;Yan Chen;J. Geller
在此之前，我们调查了对本体与当地的相似性，相应的“是一个”路径是不同的长度。这表明了将概念从一个本体导入另一个本体的可能性。我们把这种结构称为概念的菱形。在本文中，我们解决的问题是否对相同的概念对本体有相同的孩子。SNOMED CT和NCIT相对于其他八个本体的单独审查发现在儿童集的差异。我们提供有关这些差异的定量数据。在两个本体中有许多相同的孩子的情况下，问题出现了，为什么一个有更多的孩子，以及这些孩子是否在另一个本体中“失踪”。我们进行了随机对照试验，其中一位人类专家评估了这种潜在缺失的儿童概念的“适合进口”。在四项研究中的两项中，实现了支持算法导入的统计学显著性。
Previously, we investigated pairs of ontologies with local similarities where corresponding "is-a" paths are of different lengths. This indicated the possibility of importing concepts from one ontology into the other. We referred to such structures as diamonds of concepts. In this paper, we address the question whether pairs of identical concepts in pairs of ontologies have the same children in both. Separate reviews of SNOMED CT and NCIt relative to eight other ontologies uncovered differences in child sets. We provide quantitative data concerning these differences. In cases where there are many identical children in two ontologies, the questions arise why one has more children and whether these children are "missing" in the other ontology. We performed randomized controlled trials in which a human expert evaluated the "fit for import" of such potentially missing child concepts. In two out of four studies, statistical significance was achieved in support of algorithmic import.