Abstract
Finding the year of writing for a historical text is of crucial importance to historical research. However, the year of original creation is rarely explicitly stated and must be inferred from the text content, historical records, and codicological clues. Given a transcribed text, machine learning has successfully been used to estimate the year of production. In this paper, we present an overview of several estimation approaches for historical text archives spanning from the 12th century until today.- Anthology ID:
- 2021.nodalida-main.15
- Volume:
- Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)
- Month:
- May 31--2 June
- Year:
- 2021
- Address:
- Reykjavik, Iceland (Online)
- Editors:
- Simon Dobnik, Lilja Øvrelid
- Venue:
- NoDaLiDa
- SIG:
- Publisher:
- Linköping University Electronic Press, Sweden
- Note:
- Pages:
- 145–156
- Language:
- URL:
- https://aclanthology.org/2021.nodalida-main.15
- DOI:
- Cite (ACL):
- Sidsel Boldsen and Fredrik Wahlberg. 2021. Survey and reproduction of computational approaches to dating of historical texts. In Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa), pages 145–156, Reykjavik, Iceland (Online). Linköping University Electronic Press, Sweden.
- Cite (Informal):
- Survey and reproduction of computational approaches to dating of historical texts (Boldsen & Wahlberg, NoDaLiDa 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2021.nodalida-main.15.pdf
- Code
- fredrikwahlberg/nodalida21