Optimizing query answering over OWL ontologies

Kollia, I

dc.contributor.author	Kollia, I	en
dc.date.accessioned	2014-03-01T02:53:25Z
dc.date.available	2014-03-01T02:53:25Z
dc.date.issued	2011	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36300
dc.subject.other	Caching technique	en
dc.subject.other	Database technique	en
dc.subject.other	Knowledge basis	en
dc.subject.other	Ontology-based	en
dc.subject.other	OWL ontologies	en
dc.subject.other	Progressive queries	en
dc.subject.other	Query answering	en
dc.subject.other	Query answering systems	en
dc.subject.other	Reasoning tasks	en
dc.subject.other	Worst-case complexity	en
dc.subject.other	Optimization	en
dc.subject.other	Semantic Web	en
dc.subject.other	Semantics	en
dc.subject.other	User interfaces	en
dc.subject.other	World Wide Web	en
dc.subject.other	Ontology	en
dc.title	Optimizing query answering over OWL ontologies	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-21064-8_45	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-21064-8_45	en
heal.publicationDate	2011	en
heal.abstract	Query answering is a key reasoning task for many ontology based applications in the Semantic Web. Unfortunately for OWL, the worst case complexity of query answering is very high. That is why, when the schema of an ontology is written in a highly expressive language like OWL 2 DL, currently used query answering systems do not find all answers to queries posed over the ontology, i.e., they are incomplete. In this paper optimizations are discussed that may make query answering over expressive languages feasible in practice. These optimizations mostly focus on the use of traditional database techniques that will be adapted to be applicable to knowledge bases. Moreover, caching techniques and a form of progressive query answering are also explored. © 2011 Springer-Verlag Berlin Heidelberg.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-21064-8_45	en
dc.identifier.volume	6643 LNCS	en
dc.identifier.issue	PART 2	en
dc.identifier.spage	513	en
dc.identifier.epage	517	en