Projects per year
Description
Jupyter notebook to explore the model presented in the article "Word prediction in computational historical linguistics". This code is meant for educational purposes,
results may differ slightly from those presented in this paper. For the
original code used to generate the results in this paper, see https:
//bitbucket.org/pdekker/wordprediction/.
results may differ slightly from those presented in this paper. For the
original code used to generate the results in this paper, see https:
//bitbucket.org/pdekker/wordprediction/.
Abstract
Jupyter notebook to explore the model presented in the article "Word prediction in computational historical linguistics". This code is meant for educational purposes,
results may differ slightly from those presented in this paper. For the
original code used to generate the results in this paper, see https:
//bitbucket.org/pdekker/wordprediction/.
results may differ slightly from those presented in this paper. For the
original code used to generate the results in this paper, see https:
//bitbucket.org/pdekker/wordprediction/.
Date made available | 1 Feb 2021 |
---|---|
Publisher | GitHub |
Keywords
- machine learning
- historical linguistics
Format
- Format
- jupyter
- notebook
- python
- code
-
VLAAI1: Subsidie: Onderzoeksprogramma Artificiële Intelligentie (AI) Vlaanderen
1/07/19 → 31/12/24
Project: Applied
-
FWOTM1012: Identifying drivers of language change using neural agent-based models.
1/11/20 → 31/10/24
Project: Fundamental
Research output
- 1 Article
-
Word prediction in computational historical linguistics
Dekker, P. & Zuidema, W., 4 Feb 2021, In: Journal of Language Modelling. 8, 2, p. 295–336 42 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile6 Citations (Scopus)177 Downloads (Pure)