Optimizing ontology alignment through hybrid population-based incremental learning algorithm

Ontology matching is an effective technique to solve the ontology heterogeneous problem in Semantic Web. Since different ontology matchers do not necessarily find the same correct correspondences, usually several competing matchers are applied to the same pair of entities in order to increase eviden...

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Veröffentlicht in:	Memetic computing Jg. 11; H. 2; S. 209 - 217
Hauptverfasser:	Xue, Xingsi, Chen, Junfeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2019 Springer Nature B.V
Schlagworte:	Alignment Applications of Mathematics Artificial Intelligence Bioinformatics Complex Systems Control Convergence Engineering Evolutionary algorithms Machine learning Matching Mathematical and Computational Engineering Mechatronics Ontology Optimization Regular Research Paper Robotics Searching Semantic web Population-based incremental learning algorithm Ontology matching Ontology alignment evaluation initiative
ISSN:	1865-9284, 1865-9292
Online-Zugang:	Volltext
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