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叙词表本体化的陷阱——以美国国立癌症研究所叙词表为例

The Pitfalls of Thesaurus Ontologization - the Case of the NCI Thesaurus.

作者信息

Schulz Stefan, Schober Daniel, Tudose Ilinca, Stenzhorn Holger

机构信息

Medical Informatics Group, University Medical Center Freiburg, Germany.

出版信息

AMIA Annu Symp Proc. 2010 Nov 13;2010:727-31.

Abstract

Thesauri that are "ontologized" into OWL-DL semantics are highly amenable to modeling errors resulting from falsely interpreting existential restrictions. We investigated the OWL-DL representation of the NCI Thesaurus (NCIT) in order to assess the correctness of existential restrictions. A random sample of 354 axioms using the someValuesFrom operator was taken. According to a rating performed by two domain experts, roughly half of these examples, and in consequence more than 76,000 axioms in the OWL-DL version, make incorrect assertions if interpreted according to description logics semantics. These axioms therefore constitute a huge source for unintended models, rendering most logic-based reasoning unreliable. After identifying typical error patterns we discuss some possible improvements. Our recommendation is to either amend the problematic axioms in the OWL-DL formalization or to consider some less strict representational format.

摘要

被“本体化为”OWL-DL语义的叙词表极易出现因错误解释存在限制而导致的建模错误。我们研究了美国国立癌症研究所叙词表(NCIT)的OWL-DL表示形式,以评估存在限制的正确性。我们抽取了354条使用someValuesFrom运算符的公理作为随机样本。根据两位领域专家进行的评级,如果按照描述逻辑语义进行解释,这些示例中大约一半,进而OWL-DL版本中超过76,000条公理,会做出错误断言。因此,这些公理构成了意外模型的巨大来源,使得大多数基于逻辑的推理不可靠。在识别出典型错误模式后,我们讨论了一些可能的改进措施。我们的建议是要么修正OWL-DL形式化中的问题公理,要么考虑一些不太严格的表示格式。

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