DC FieldValueLanguage
dc.contributor.authorChrysanthopoulos, Christos-
dc.contributor.authorStoyannidis, Yannis-
dc.contributor.authorTriantafyllou, Ioannis-
dc.contributor.authorTsolakidis, Anastasios-
dc.date.accessioned2023-10-12T21:25:02Z-
dc.date.available2023-10-12T21:25:02Z-
dc.date.issued2023-
dc.identifier.otherdBpJUcoAAAAJ:roLk4NBRz8UC-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/244-
dc.description.abstractPurpose - This paper explores the goal and potential of integrating machine learning technologies into archives and records management practices. As the volume and complexity of digital records continue to grow, traditional methods of organising, classifying, and managing records face new challenges. Machine learning technologies offer opportunities to revolutionise how records are maintained, accessed, and used. Design/methodology/approach - The relationship between records and archive management and machine learning practices is presented through the literature. This paper proposes a case study implementation of machine learning practices for the subject classification of records at the University of West Attica. Findings - This paper presents a research hypothesis placing the subject classification of records at the center of the discussion. It highlights the necessity of deepening the standardisation of government actions record management processes. Originality/value - By exploring this topic, the paper seeks to contribute to a deeper understanding of the transformative role that machine learning technologies can play in archives and records management and to inform future practices and decision-making in the field. It is also the first theoretical part of an ongoing research project on the subject classification of the University of West Attica records.en_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Integrated Information Managementen_US
dc.sourceJournal of Integrated Information Management 8 (1), 7-13, 2023-
dc.subjectArchives and records managementen_US
dc.subjectMachine learningen_US
dc.subjectComputational archival scienceen_US
dc.subjectUniversity archivesen_US
dc.subjectSubject classificationen_US
dc.titleArchives and records management in machine learning technologies context: a research hypothesis on university recordsen_US
dc.typeArticleen_US
dc.identifier.doi10.26265/jiim.v8i1.4517en_US
dc.relation.deptDepartment of Archival, Library and Information Studiesen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume8en_US
dc.relation.issue1en_US
dc.identifier.spage7en_US
dc.identifier.epage13en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldSocial Sciencesen_US
dc.journalsOpen Accessen_US
dc.countryGreeceen_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeArticle-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.deptDepartment of Archival, Library and Information Studies-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0001-9551-8360-
crisitem.author.orcid0000-0001-5273-0855-
crisitem.author.orcid0000-0001-7364-4542-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
Appears in Collections:Articles / Άρθρα
CORE Recommender
Show simple item record

Page view(s)

54
checked on Nov 23, 2024

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.