Detection of Contextual Identity Links in a Knowledge Base

被引：5
|
作者：
Raad, Joe [1 ]
Pernelle, Nathalie [2 ]
Sais, Fatiha [2 ]
机构：
[1] INRA, UMR 518, Paris, France
[2] Paris Sud Univ, LRI, Orsay, France
来源：
K-CAP 2017: PROCEEDINGS OF THE KNOWLEDGE CAPTURE CONFERENCE | 2017年
关键词：
context; identity link discovery; scientific data;
D O I：
10.1145/3148011.3148032
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Most of the Linked Data applications currently rely on the use of owl : sameAs for linking ontology instances. However, several studies have noticed multiple misuses of this identity link. These misuses, which are mainly caused by the lack of other well-defined linking alternatives, can lead to erroneous statements or inconsistencies. We propose in this paper a new contextual identity link: identiConTo that could serve as a replacement for owl : sameAs in linking identical instances in a specified context. To detect these contextual links, we have defined an algorithm named DECIDE that has been tested on scientific knowledge bases describing transformation processes.
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页数：8
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