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Low-Resource Techniques for Analysing the Rhetorical Structure of Swedish Historical Petitions
Uppsala University, Sweden.
Uppsala University, Sweden.
RISE Research Institutes of Sweden, Digital Systems, Data Science. Uppsala University, Sweden.ORCID iD: 0000-0002-7873-3971
2023 (English)In: RESOURCEFUL 2023 - Workshop on Resources and Representations for Under-Resourced Languages and Domains, Proceedings of the 2nd, Association for Computational Linguistics , 2023, p. 132-139Conference paper, Published paper (Refereed)
Abstract [en]

Natural language processing techniques can be valuable for improving and facilitating historical research. This is also true for the analysis of petitions, a source which has been relatively little used in historical research. However, limited data resources pose challenges for mainstream natural language processing approaches based on machine learning. In this paper, we explore methods for automatically segmenting petitions according to their rhetorical structure. We find that the use of rules, word embeddings, and especially keywords can give promising results for this task.

Place, publisher, year, edition, pages
Association for Computational Linguistics , 2023. p. 132-139
Keywords [en]
Computational linguistics; Image segmentation; Natural language processing systems; Text processing; Data resources; Historical research; Language processing; Language processing techniques; Limited data; Natural languages; On-machines; Processing approach; Rhetorical structure; Swedishs; Learning algorithms
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-67997Scopus ID: 2-s2.0-85175852005OAI: oai:DiVA.org:ri-67997DiVA, id: diva2:1814311
Conference
2nd Workshop on Resources and Representations for Under-Resourced Languages and Domains, RESOURCEFUL 2023. Torshavn, Denmark. 22 May 2023
Note

The research reported in this paper was supported by a grant from the Swedish Research Council (grant number 2018-06159).

Available from: 2023-11-24 Created: 2023-11-24 Last updated: 2023-11-24Bibliographically approved

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Nivre, Joakim

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Citation style
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Language
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  • nn-NB
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Output format
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