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  • Dekker, P., & Zuidema, W. (2021). Word prediction in computational historical linguistics. Journal of Language Modelling, 8(2), 295–336. [pdf] [code]
  • 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., Tavakolpoursaleh, N., Schaer, P., Chuang, P-Y., Wu, J., & Giles, C.L. (2016). Overview of the TREC 2016 Open Search track: Academic Search Edition. In E.M. Voorhees & A. Ellis (Eds.) Proceedings of the Twenty-Fifth Text REtrieval Conference (TREC 2016). NIST. [pdf]
  • Dekker, P. (2014). Determining Dutch dialect phylogeny using bayesian inference (Bachelor’s thesis). Utrecht University. [pdf] [html alignments]

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