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Towards a Similarity Algorithm for Controlled Vocabularies Within the Digital Humanities

Ernst, Felix ORCID iD icon 1
1 Scientific Computing Center (SCC), Karlsruher Institut für Technologie (KIT)

Abstract:

With a growing amount and increasing complexity of data and metadata in the Digital Humanities, the use of semantic tools such as controlled vocabularies and taxonomies becomes more and more important to gain new research insights. Their use enables new research possibilities by introducing machine readable semantic links and standardised data and metadata. A validation and recommender system that ensures a quick development of high quality vocabularies is essential in such a scientific workflow. The base of this system is a similarity algorithm. State of the art algorithms and editors for controlled vocabularies do not meet the special requirements of the Digital Humanities domain. Therefore, this work proposes to fill the research gap in the Digital Humanities domain with a similarity algorithm and a recommender and validation system for controlled vocabularies. The methodology and evaluation for achieving this goal as well as preliminary results are presented in this contribution.


Preprint §
DOI: 10.5445/IR/1000149752
Veröffentlicht am 19.12.2022
Cover der Publikation
Zugehörige Institution(en) am KIT Scientific Computing Center (SCC)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2022
Sprache Englisch
Identifikator ISBN: 978-3-031-11609-4
ISSN: 0302-9743, 1611-3349
KITopen-ID: 1000149752
HGF-Programm 46.21.02 (POF IV, LK 01) Cross-Domain ATMLs and Research Groups
Erschienen in The Semantic Web: ESWC 2022 Satellite Events ; Hersonissos, Crete, Greece, May 29 – June 2, 2022, Proceedings. Ed.: P. Groth
Veranstaltung European Semantic Web Conference (ESWC 2022), Hersonissos, Griechenland, 29.05.2022 – 02.06.2022
Verlag Springer International Publishing
Seiten 179–188
Serie Lecture Notes in Computer Science (LNCS) ; 13384
Vorab online veröffentlicht am 20.07.2022
Schlagwörter Semantic Web, Similarity metrics, Recommender system, Controlled vocabularies, Vocabulary editor, SKOS
Nachgewiesen in Dimensions
Scopus
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