Learning ontology alignments using recursive neural networks

Chortaras, A; Stamou, G; Stafylopatis, A

dc.contributor.author	Chortaras, A	en
dc.contributor.author	Stamou, G	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T02:43:23Z
dc.date.available	2014-03-01T02:43:23Z
dc.date.issued	2005	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31383
dc.subject	Knowledge Representation	en
dc.subject	Ontology Alignment	en
dc.subject	Recursive Neural Networks	en
dc.subject	Semantic Mapping	en
dc.subject	Semantic Web	en
dc.subject	Structured Data	en
dc.subject	Neural Network	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.other	Information analysis	en
dc.subject.other	Knowledge representation	en
dc.subject.other	Multimedia systems	en
dc.subject.other	Neural networks	en
dc.subject.other	Semantics	en
dc.subject.other	World Wide Web	en
dc.subject.other	Multimedia information	en
dc.subject.other	Non-identical ontologies	en
dc.subject.other	Ontology alignment tools	en
dc.subject.other	Web machines	en
dc.subject.other	Computer science	en
dc.title	Learning ontology alignments using recursive neural networks	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/11550907_128	en
heal.identifier.secondary	http://dx.doi.org/10.1007/11550907_128	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	The Semantic Web is based on technologies that make the content of the Web machine-understandable. In that framework, ontological knowledge representation has become an important tool for the analysis and understanding of multimedia information. Because of the distributed nature of the Semantic Web however, ontologies describing similar fields of knowledge are being developed and the data coming from similar but non-identical ontologies can be combined only if a semantic mapping between them is first established. This has lead to the development of several ontology alignment tools. We propose an automatic ontology alignment method based on the recursive neural network model that uses ontology instances to learn similarities between ontology concepts. Recursive neural networks are an extension of common neural networks, designed to process efficiently structured data. Since ontologies are a structured data representation, the model is inherently suitable for use with ontologies. © Springer-Verlag Berlin Heidelberg 2005.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
heal.bookName	LECTURE NOTES IN COMPUTER SCIENCE	en
dc.identifier.doi	10.1007/11550907_128	en
dc.identifier.isi	ISI:000232196000128	en
dc.identifier.volume	3697 LNCS	en
dc.identifier.spage	811	en
dc.identifier.epage	816	en