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Making Non-Normalized Content Retrievable – A Tagging Pipeline for a Corpus of Expert-Layperson Texts

  • Conventional terminology resources reach their limits when it comes to automatic content classification of texts in the domain of expertlayperson communication. This can be attributed to the fact that (non-normalized) language usage does not necessarily reflect the terminological elements stored in such resources. We present several strategies to extend a terminological resource with term-related elements in order to optimize automatic content classification of expert-layperson texts.

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Metadaten
Author:Christian LangGND, Ngoc Duyen Tanja TuORCiDGND, Laura Zeidler
URN:urn:nbn:de:bsz:mh39-121941
DOI:https://doi.org/https://doi.org/10.34619/srmk-injj
ISBN:978-989-54081-5-3
Parent Title (English):Language, Data and Knowledge 2023 (LDK 2023): Proceedings of the 4th Conference on Language, Data and Knowledge
Publisher:NOVA FCSH - CLUNL
Place of publication:Portugal
Editor:Sara Carvalho, Anas Fahad Khan, Ana Ostroški Anić, Blerina Spahiu, Jorge Gracia, John P. McCrae, Dagmar Gromann, Barbara Heinisch, Ana Salgado
Document Type:Part of a Book
Language:English
Year of first Publication:2023
Date of Publication (online):2023/10/23
Publishing Institution:Leibniz-Institut für Deutsche Sprache (IDS)
Publicationstate:Veröffentlichungsversion
Reviewstate:Peer-Review
GND Keyword:Experte; Kommunikation; Laie; Sprachgebrauch; Terminologie; Text
First Page:239
Last Page:244
DDC classes:400 Sprache / 400 Sprache, Linguistik
Open Access?:ja
BDSL-Classification:Grammatik
Leibniz-Classification:Sprache, Linguistik
Linguistics-Classification:Grammatikforschung
Program areas:G2: Sprachinformationssysteme
Licence (English):License LogoCreative Commons - Attribution 4.0 International