Automatic link-detection in Encoded Archival Descriptions
Year: 2008
Type: conference-paper
Abstract: In this paper we investigate how currently emerging link detection methods can help enrich encoded archival descriptions. We discuss link detection methods in general, and evaluate the identification of names both within, and across, archival descriptions. Our initial experiments suggest that we can automatically detect occurrences of person names with high accuracy, both within (F-score of 0.9620) and across (F-score of 1) archival descriptions. This allows us to create (pseudo) encoded archival context descriptions that provide novel means of navigation, improving access to the vast amounts of archival data.
Authors: Junte Zhang, Khairun Nisa Fachry, Jaap Kamps
Language: English
Subfield: Conservation
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: green
Funders: National Science Foundation, Institute of Museum and Library Services, Andrew W. Mellon Foundation, Fonds Wetenschappelijk Onderzoek, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Cambridge Institute for Medical Research, University of Cambridge, Japan Society for the Promotion of Science
OpenAlex ID: W2169869453