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How Lexical Gold Standards Have Effects on the Usefulness of Text Analysis Tools for Digital Scholarship
KTH, Superseded Departments (pre-2005), Computer and Systems Sciences, DSV.ORCID iD: 0000-0003-4042-4919
2019 (English)In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): International Conference of the Cross-Language Evaluation Forum for European Languages CLEF 2019: Experimental IR Meets Multilinguality, Multimodality, and Interaction, 2019, p. 178-184Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes how the current lexical similarity and analogy gold standards are built to conform to certain ideas about what the models they are designed to evaluate are used for. Topical relevance has always been the most important target notion for information access tools and related language technology technologies, and while this has proven a useful starting point for much of what information technology is used for, it does not always align well with other uses to which technologies are being put, most notably use cases from digital scholarship in the humanities or social sciences. This paper argues for more systematic formulation of requirements from the digital humanities and social sciences and more explicit description of the assumptions underlying model design.

Place, publisher, year, edition, pages
2019. p. 178-184
National Category
Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:kth:diva-268334DOI: 10.1007/978-3-030-28577-7_14Scopus ID: 2-s2.0-85072842110OAI: oai:DiVA.org:kth-268334DiVA, id: diva2:1413268
Conference
10th International Conference of the CLEF Association, CLEF 2019, Lugano, Switzerland, September 9–12, 2019
Note

QC 20200310

Available from: 2020-03-10 Created: 2020-03-10 Last updated: 2020-03-10Bibliographically approved

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Publisher's full textScopushttps://link.springer.com/chapter/10.1007%2F978-3-030-28577-7_14

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Karlgren, Jussi

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