Class expression learning for ontology engineering

被引:77
作者
Lehmann, Jens [1 ]
Auer, Soeren [1 ]
Buehmann, Lorenz [1 ]
Tramp, Sebastian [1 ]
机构
[1] Univ Leipzig, Dept Comp Sci, D-04103 Leipzig, Germany
来源
JOURNAL OF WEB SEMANTICS | 2011年 / 9卷 / 01期
关键词
Ontology engineering; Supervised machine learning; Concept learning; Ontology editor plugins; OWL; Heuristics; SEMANTIC WEB;
D O I
10.1016/j.websem.2011.01.001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
While the number of knowledge bases in the Semantic Web increases, the maintenance and creation of ontology schemata still remain a challenge. In particular creating class expressions constitutes one of the more demanding aspects of ontology engineering. In this article we describe how to adapt a semiautomatic method for learning OWL class expressions to the ontology engineering use case. Specifically, we describe how to extend an existing learning algorithm for the class learning problem. We perform rigorous performance optimization of the underlying algorithms for providing instant suggestions to the user. We also present two plugins, which use the algorithm, for the popular Protege and OntoWiki ontology editors and provide a preliminary evaluation on real ontologies. (C) 2011 Elsevier B. V. All rights reserved.
引用
收藏
页码:71 / 81
页数:11
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