Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16254
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dc.contributor.authorIVANOVA, Krassimira-
dc.contributor.authorVelychko, Vitalii-
dc.contributor.authorMARKOV, Krassimir-
dc.date.accessioned2014-01-31T08:49:05Z-
dc.date.available2014-01-31T08:49:05Z-
dc.date.issued2012-
dc.identifier.citationSetlak, Galina; Alexandrov, Mikhail; Markov, Krassimir (Ed.). Artificial Intelligence Methods and Techniques for Business and Engineering Applications, ITHEA® 2012, p. 84 -98-
dc.identifier.isbn978-954-16-0057-3-
dc.identifier.urihttp://hdl.handle.net/1942/16254-
dc.description.abstractNL-addressing is a possibility to access information using natural language words as addresses of the information stored in the multi-dimensional numbered information spaces. For this purpose the internal encoding of the letters is used to generate corresponded co-ordinates. The tool for working in such style is named OntoArM. Its main principles, functions and using for storing RDF graphs are outlined in this paper-
dc.language.isoen-
dc.publisherITHEA® 2012-
dc.subject.otherNL-addressing, RDF graphs, ontology representations.-
dc.titleStoring RDF Graphs using NL-addressing-
dc.typeBook Section-
local.bibliographicCitation.authorsSetlak, Galina-
local.bibliographicCitation.authorsAlexandrov, Mikhail-
local.bibliographicCitation.authorsMarkov, Krassimir-
dc.identifier.epage98-
dc.identifier.spage84-
local.bibliographicCitation.jcatB1-
local.publisher.placeRzeszow, Poland; Sofia, Bulgaria-
local.type.specifiedBook Section-
local.provider.typePdf-
local.bibliographicCitation.btitleArtificial Intelligence Methods and Techniques for Business and Engineering Applications-
item.accessRightsOpen Access-
item.contributorIVANOVA, Krassimira-
item.contributorVelychko, Vitalii-
item.contributorMARKOV, Krassimir-
item.fulltextWith Fulltext-
item.fullcitationIVANOVA, Krassimira; Velychko, Vitalii & MARKOV, Krassimir (2012) Storing RDF Graphs using NL-addressing. In: Setlak, Galina; Alexandrov, Mikhail; Markov, Krassimir (Ed.). Artificial Intelligence Methods and Techniques for Business and Engineering Applications, ITHEA® 2012, p. 84 -98.-
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