DocumentCode
2028758
Title
Detecting Ontology Mappings via Descriptive Statistical Methods
Author
Todorov, Konstantin
Author_Institution
Inst. of Cognitive Sci., Universtity of Osnabruck, Osnabruck
fYear
2009
fDate
24-28 May 2009
Firstpage
177
Lastpage
182
Abstract
Instance-based ontology mapping comprises a collection of theoretical approaches and applications for identifying the implicit semantic similarities between two ontologies on the basis of the instances that populate their concepts. The current paper situates this general problem in the realm of finding mappings between the nodes of two different Web directories populated with text documents (the Web pages that they intend to organize). We propose a novel approach to detect potential concept mappings based on principle component analysis and discriminant analysis and introduce a resulting concept similarity measure. The procedure can be used as an independent concept mapping technique, or as a support to a concept similarity measure of other nature.
Keywords
Internet; ontologies (artificial intelligence); principal component analysis; text analysis; Web directories; concept mappings; descriptive statistical methods; discriminant analysis; instance-based ontology mapping; principle component analysis; semantic similarities; text documents; Cognitive science; Independent component analysis; Ontologies; Performance evaluation; Statistical analysis; Taxonomy; Web and internet services; Web pages; Concept Similarity; Descriptive Statistics; Instance-based Ontology Mapping; Machine Learning; Ontologies;
fLanguage
English
Publisher
ieee
Conference_Titel
Internet and Web Applications and Services, 2009. ICIW '09. Fourth International Conference on
Conference_Location
Venice/Mestre
Print_ISBN
978-1-4244-3851-8
Electronic_ISBN
978-0-7695-3613-2
Type
conf
DOI
10.1109/ICIW.2009.33
Filename
5072516
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