Ontology Alignment with Weightless Neural Networks

被引：2

作者：

Viana, Thais ^{[1
]}

Delgado, Carla ^{[1
,2
]}

da Silva, Joao C. P. ^{[2
]}

Lima, Priscila ^{[1
]}

机构：

[1] Univ Fed Rio de Janeiro, Program Posgrad Informat, Rio De Janeiro, Brazil

[2] Univ Fed Rio de Janeiro, Dept Ciencia Comp, IM, Ave Athos da Silveira Ramos 274, BR-68530 Rio De Janeiro, Brazil

来源：

ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, PT II | 2017年 / 10614卷

关键词：

Weightless Neural Network; WiSARD; Ontology alignment; Ontology matching;

D O I：

10.1007/978-3-319-68612-7_43

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present an ontology matching process based on the usage of Weightless Neural Networks (WNN). The alignment of ontologies for specific domains provides several benefits, such as interoperability among different systems and the improvement of the domain knowledge derived from the insights inferred from the combined information contained in the various ontologies. A WiSARD classifier is built to estimate a distribution-based similarity measure among the concepts of the several ontologies being matched. To validate our approach, we apply the proposed matching process to the knowledge domain of algorithms, software and computational problems, having some promising results.

引用

页码：376 / 384

页数：9

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