See also my profiles on: ResearchGate | Academia.edu | Google Scholar | VUB.
Academic
- Dekker, P. & Zuidema, W. (2020). Word Prediction in Computational Historical Linguistics. Journal of Language Modelling (forthcoming).
- Creten, S., Dekker, P., & Vandeghinste, V. (2020). Linguistic Enrichment of Historical Dutch using Deep Learning. Computational Linguistics in the Netherlands Journal, 10, 57-72. [pdf]
- Dekker, P. & Schoonheim, T. (2018). Crowdsourcing Language Resources for Dutch using PYBOSSA: Case Studies on Blends, Neologisms and Language Variation. In Proceedings of the enetCollect WG3&WG5 Meeting, 24-25 October 2018, Leiden, Netherlands. [pdf]
- Dekker, P. (2018). Reconstructing language ancestry by performing word prediction with neural networks (Master’s thesis). [pdf]
- Balog, K., Schuth, A., Dekker, P., Schaer, P., Chuang, P., & Tavakolpoursaleh, N. (2016). Overview of the TRECT 206 Open Search track. In E.M. Voorhees & A. Ellis (Eds.) Proceedings of the Twenty-Fifth Text REtrieval Conference (TREC 2016). NIST. [pdf] [bib]
- Dekker, P. (2014). Determining Dutch dialect phylogeny using bayesian inference (Bachelor’s thesis). Utrecht University. [pdf] [bib] [html alignments]
Blogs
- Neural networks help discover how languages are related, blog on MSc thesis, ILLC CLC Lab website, 19-11-2019.
- Ga lekker zitten, Dutch blog on usage of lekker using crowdsourcing research, with Laura van Eerten, Neerlandistiek.nl, 28-02-2019.