A Library Perspective on Nearly-Unsupervised Information Extraction Workflows in Digital Libraries

TitleA Library Perspective on Nearly-Unsupervised Information Extraction Workflows in Digital Libraries
Publication TypeConference Paper
Year of Publication2022
AuthorsKroll, H., J. Pirklbauer, F. Plötzky, and W. - T. Balke
Conference NameACM/IEEE Joint Conference on Digital Libraries (JCDL)
Date Published06/2022
Conference LocationCologne, Germany
Abstract

Information extraction can support novel and effective access paths for digital libraries. Nevertheless, designing reliable extraction workflows can be cost-intensive in practice. On the one hand, suitable extraction methods rely on domain-specific training data. On the other hand, unsupervised and open extraction methods usually produce not-canonicalized extraction results. This paper tackles the question how digital libraries can handle such extractions and if their quality is sufficient in practice. We focus on unsupervised extraction workflows by analyzing them in case studies in the domains of encyclopedias (Wikipedia), pharmacy and political sciences. We report on opportunities and limitations. Finally we discuss best practices for unsupervised extraction workflows.

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