Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/2378
DC FieldValueLanguage
dc.contributor.authorKovačević, Jovanaen_US
dc.contributor.authorGraovac, Jelenaen_US
dc.date.accessioned2025-08-27T16:02:33Z-
dc.date.available2025-08-27T16:02:33Z-
dc.date.issued2016-
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/2378-
dc.description.abstractThe paper presents a proposal of a method for hierarchical classification of digitized documents of NCD digital library. The classification model implements Structured Support Vector Machine method (SSVM) which has shown excellent performance on Ebart corpus of documents in Serbian language. We describe the developed model and its results on Ebart dataset, suggest two types of hierarchies of classes of the NCD library regarding its content and define a protocol for the application of the method to digitized documents.en_US
dc.language.isoenen_US
dc.publisherBeograd : Matematički fakulteten_US
dc.relation.ispartofPregled Nacionalnog centra za digitalizacijuen_US
dc.subjecthierarchical text classificationen_US
dc.subjectstructured support vector machine methoden_US
dc.subjectn-gramsen_US
dc.subjectEbarten_US
dc.titleProspective automated hierarchical classification of digitized documentsen_US
dc.typeArticleen_US
dc.identifier.urlhttp://elib.mi.sanu.ac.rs/files/journals/ncd/29/ncdn29p42-51.pdf-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.issn1820-0109en_US
dc.description.rankM53en_US
dc.relation.firstpage42en_US
dc.relation.lastpage51en_US
dc.relation.volume29en_US
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeArticle-
item.cerifentitytypePublications-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.orcid0000-0002-0242-2472-
crisitem.author.orcid0000-0002-9323-4695-
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