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Title: Transforming archival description into semantically enriched form using machine learning Authors: ID Sabadin, Ivančica (Author) Files: https://journal.almamater.si/index.php/atlantiplus/issue/view/51/41   Sabadin_Ivancica.pdf (6,40 MB) MD5: 6C0B11CC4251FF9E9487E703EB5A6AED   Language: English Work type: Unknown Typology: 1.01 - Original Scientific Article Organization: UAMEU - Alma Mater Europaea University Abstract: Purpose: The purpose of this paper is to determine if it is possible to transform the archival description in the relational database into an ontology with a ma-chine learning algorithm. Method/approach: The research will be based on the CRISP-ML(Q) method. The following steps will be carried out: Business and data understanding; Data preparation; Modelling and Evaluation.Results: After the transformation of the archival description, the Random Forest classification was used to predict the predicate in the semantic triplets. The re-sults obtained were: precision: 86.1% and accuracy: 96.5%.Conclusions / findings: Based on the results, we can conclude that the hypoth-esis was confirmed and that the machine learning algorithms are suitable for transforming the archival description in a structured form into an ontology. Keywords: archival description, semantical enrichment, machine learning, RiC-O ontology, KNIME Publication date: 01.01.2025 Year of publishing: 2025 Number of pages: Str. 45-69 Numbering: [Vol.] 35, [no.] 1 PID: 20.500.12556/ReVIS-14124  COBISS.SI-ID: 250077443  UDC: 930.25:004(4) ISSN on article: 2670-4560 Publication date in ReVIS: 01.07.2026 Views: 47 Downloads: 0 Metadata:    Cite this work Plain text BibTeX EndNote XML EndNote/Refer RIS ABNT ACM Ref AMA APA Chicago 17th Author-Date Harvard IEEE ISO 690 MLA Vancouver : Copy citation

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Record is a part of a journal

Title:	Atlanti + : international scientific review for contemporary archival theory and practice
Publisher:	International Institute for Archival Science, Alma Mater Europaea - European Center Maribor
ISSN:	2670-4560
COBISS.SI-ID:	299197440

Secondary language

Language:	Slovenian
Keywords:	arhivski opis, semantična obogatitev, strojno učenje, RiC-O ontologija, KNIME

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