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Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/679
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dc.contributor.authorKartelj, Aleksandaren_US
dc.contributor.authorFilipović, Vladimiren_US
dc.contributor.authorMilutinović, Veljkoen_US
dc.date.accessioned2022-08-14T09:49:37Z-
dc.date.available2022-08-14T09:49:37Z-
dc.date.issued2012-08-23-
dc.identifier.isbn9789532330724-
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/679-
dc.description.abstractIn this paper, we propose several new research directions regarding the problem of Automated Personality Classification (APC). Firstly, we investigate possible improvements of the existing solutions to the problem of APC, for which we use different combinations of the APC corpora, psychological trait measurements, and learning algorithms. Afterwards, we consider extensions of the APC problem and the related tasks, such as dynamical APC and detecting personality inconsistency in a text. This entire research was performed in the context of social networks and the related datamining mechanisms. © 2012 MIPRO.en
dc.titleNovel approaches to automated personality classification: Ideas and their potentialsen_US
dc.typeConference Paperen_US
dc.relation.publicationMIPRO 2012 - 35th International Convention on Information and Communication Technology, Electronics and Microelectronics - Proceedingsen_US
dc.identifier.scopus2-s2.0-84865127929-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84865127929-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.firstpage1017en_US
dc.relation.lastpage1022en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairetypeConference Paper-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.orcid0000-0001-9839-6039-
crisitem.author.orcid0000-0002-5943-8037-
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