基于差异的身份链接失效方法

Anderson Carlos Ferreira Da Silva, Fatiha Saïs, E. Waller, F. Andrès
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引用次数: 1

摘要

目前越来越多的数据集使用owl:sameAs等属性通过身份链接连接起来。标识链接是声明两个资源引用同一个现实世界实体的语句。但是,我们无法证明所有身份链接的正确性。在没有中央名称权威的情况下,大多数身份链接都是由启发式生成的,并且没有经过专家的审查。使身份链接失效的主要问题是数据集的异构性,它们通常不共享相同的谓词。此外,资源的描述可能是不完整的。无论如何描述资源,身份链接都是链接数据以供以后使用的必要条件。在本文中,我们提出了一种利用等价类中的不相似点检测和离群点检测来判定身份链路无效的框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dissimilarity-based approach for Identity Link Invalidation
More and more datasets are currently connected by identity links using properties such as owl:sameAs expressed in OWL. Identity links are statements that declare that two resources refer to the same real-world entity. However, we cannot attest the correctness of all identity links. Without a central name authority, most identity links are generated by heuristics and they are not reviewed by experts. The main issue in invalidating identity links is the heterogeneity of datasets, they commonly do not share the same predicates. Furthermore, the description of the resources can be incomplete. Despite how the resources are described, identity links are necessary to link data for posterior use. In this paper, we present a framework to invalidate identity links by dissimilarity and outlier detection in equivalence classes of identity links.
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