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Dr. M.P. (Marijn) Schraagen

Junior universitair docent 
Bètawetenschappen
Informatica
AI & Data Science
Natural Language Processing
Natural Language Processing
Buys Ballotgebouw
Princetonplein 5
Kamer 5.01
3584 CC Utrecht

Dr. M.P. (Marijn) Schraagen

Junior universitair docent
Natural Language Processing
m.p.schraagen@uu.nl
Profiel Publicaties Activiteiten Onderzoek Onderwijs Contact
Profiel Publicaties Activiteiten Onderzoek Onderwijs Contact

Publicaties

2023

Wetenschappelijke publicaties

van Es, B., Reteig, L., Tan, S., Schraagen, M., Hemker, M., Arends, S., Rios, M., & Haitjema, S. (2023). Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods. BMC Bioinformatics, 24(1), 1-20. Article 10. https://doi.org/10.1186/s12859-022-05130-x
Toledo, C. V., Schraagen, M., Dijk, F. V., Brinkhuis, M., & Spruit, M. (2023). Readability Metrics for Machine Translation in Dutch: Google vs. Azure & IBM. Applied Sciences, 13(7), 1-14. Article 4444. https://doi.org/10.3390/app13074444
Yew, A., Schraagen, M., Otte, W. M., & van Diessen, E. G. A. L. (2023). Transforming epilepsy research: A systematic review on natural language processing applications. Epilepsia, 64(2), 292-305. https://doi.org/10.1111/epi.17474

2022

Wetenschappelijke publicaties

Wegmann, A., Schraagen, M., & Nguyen, D. (2022). Same Author or Just Same Topic? Towards Content-Independent Style Representations. In Proceedings of the 7th Workshop on Representation Learning for NLP (pp. 249-268). Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.repl4nlp-1.26
van de Luijtgaarden, N., Prijs, D., Schraagen, M., & Bex, F. (2022). Abstractive Summarization of Dutch Court Verdicts Using Sequence-to-sequence Models. In Proceedings of the Natural Legal Language Processing Workshop 2022 ACL Anthology.
Dietz, F., van Koppen, M., van de Poppe, C., Schraagen, M., & Wall, J. (2022). Cross-disciplinary approaches to linguistic variation in Early Modern West Germanic. Journal of Historical Syntax, 6, 1-23. Article 13. https://doi.org/10.18148/hs/2022.v7i13-18.167
https://dspace.library.uu.nl/bitstream/handle/1874/426039/Introduction_Language_Dynamics_JHS.pdf?sequence=1
van Toledo, C., Schraagen, M., van Dijk, F. W., Brinkhuis, M., & Spruit, M. (2022). Exploring the Utility of Dutch Question Answering Datasets for Human Resource Contact Centres. Information, 13(11), 1-11. Article 513. https://doi.org/10.3390/info13110513
Zhang, C., Wang, S., Tjong Kim Sang, E., Adriaanse, M. A., Tummers, L., Schraagen, M., Qi, J., Dastani, M., & Aarts, H. (2022). Spatiotemporal variations of public opinion on social distancing in the Netherlands: Comparison of Twitter and longitudinal survey data. Frontiers in Public Health, 10, 1-14. Article 856825. https://doi.org/10.3389/fpubh.2022.856825

Vakpublicaties

Dietz, F., van Koppen, M., Schraagen, M., & Wall, J. (2022). Special issue: Cross-disciplinary approaches to linguistic variation in Early Modern West Germanic. Journal of Historical Syntax, 6(13-18).

2020

Wetenschappelijke publicaties

Schraagen, M. P., Wall, J. H., & Brito, E. (2020). The CLIN30 shared task: Have-doubling in historical varieties of Dutch. Computational Linguistics in The Netherlands journal, 10, 161-178. https://www.clinjournal.org/clinj/article/view/115
Odijk, J., Deoskar, T., Klis, M. V. D., & Schraagen, M. (2020). Preface. Computational Linguistics in The Netherlands journal, 10, 1-3. https://www.clinjournal.org/clinj/article/view/99/89
Wang, S., Schraagen, M., Tjong Kim Sang, E., & Dastani, M. (2020). Public Sentiment on Governmental COVID-19 Measures in Dutch Social Media. In K. Verspoor, K. Bretonnel Cohen, M. Conway, B. de Bruijn, M. Dredze, R. Mihalcea, & B. Wallace (Eds.), Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at the 2020 Conference on Empirical Methods in Natural Language Processing Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2020.nlpcovid19-2.17

2019

Wetenschappelijke publicaties

Schraagen, M. P., & Bex, F. J. (2019). Extraction of semantic relations in noisy user-generated law enforcement data. In Proceedings of the 13th IEEE International Conference on Semantic Computing (pp. 79-86). IEEE. https://doi.org/10.1109/ICSC.2019.00020

2018

Wetenschappelijke publicaties

Schraagen, M. P., Dietz, F. M., & van Koppen, J. M. (2018). Linguistic and Sociolinguistic Annotation of 17th Century Dutch Letters. In N. Calzolari (Ed.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation (pp. 1146-1152). European Language Resources Association (ELRA). https://aclanthology.info/papers/L18-1184/l18-1184
Schraagen, M. P., Bex, F. J., Odekerken, D., & Testerink, B. J. G. (Accepted/In press). Argumentation-driven information extraction for online crime reports. In International Workshop on Legal Data Analysis and Mining (LeDAM 2018) (CEUR workshop proceedings).

2017

Wetenschappelijke publicaties

Kos, W., Schraagen, M. P., Brinkhuis, M. J. S., & Bex, F. J. (2017). Classification in a Skewed Online Trade Fraud Complaint Corpus. In B. Verheij, & M. Wiering (Eds.), Preproceedings of the 29th Benelux Conference on Artificial Intelligence November 8–9, 2017 in Groningen, The Netherlands: BNAIC 2017 (pp. 172-183)
https://dspace.library.uu.nl/bitstream/handle/1874/356746/Kos_bnaic_preproceedings.pdf?sequence=1
Schraagen, M. P., Brinkhuis, M. J. S., & Bex, F. J. (2017). Evaluation of Named Entity Recognition in Dutch Online Criminal Complaints. Unpublished. In ICAIL 2017 workshop on Discovery of Electronically Stored Information (DESI VII)
https://dspace.library.uu.nl/bitstream/handle/1874/429601/NER_Eval_Schraagen_et_al_final.pdf?sequence=1
Tjong Kim Sang, E., Bollman, M., Boschker, R., Casacuberta, F., Dietz, F. M., Dipper, S., Domingo, M., van der Goot, R., van Koppen, J. M., Ljubešić, N., Östling, R., Petran, F., Pettersson, E., Scherrer, Y., Schraagen, M. P., Sevens, L., Tiedeman, J., Vanallemeersch, T., & Zervanou, K. (2017). The CLIN27 Shared Task: Translating Historical Text to Contemporary Language for Improving Automatic Linguistic Annotation. Computational Linguistics in The Netherlands journal, 7, 53-64. https://clinjournal.org/clinj/article/view/68
https://dspace.library.uu.nl/bitstream/handle/1874/360876/04.clin27_shared_task.pdf?sequence=1
Schraagen, M. P., Dietz, F. M., van Koppen, J. M., & Kramer, I. (2017). Corpus enrichment for 17th century Dutch: a pilot study. In Proceedings of DHBenelux 2017: Tuesday (pp. 68-71). Article L-3 Utrecht University.
https://dspace.library.uu.nl/bitstream/handle/1874/356059/Schraagen_DHBenelux_2017.pdf?sequence=1
Schraagen, M. P., van Koppen, J. M., & Dietz, F. M. (2017). Data-driven Morphology and Sociolinguistics for Early Modern Dutch. In G. Bouma, & Y. Adesam (Eds.), NEALT Proceedings Series: Proceedings of the NoDaLiDa 2017 Workshop on Processing Historical Language (Vol. 32, pp. 47-53). Linköping University Electronic Press, Linköpings universitet.
https://dspace.library.uu.nl/bitstream/handle/1874/356058/Schraagen_NoDaLiDa_2017.pdf?sequence=1
Schraagen, M. P., Brinkhuis, M. J. S., & Bex, F. J. (2017). Evaluation of Named Entity Recognition in Dutch online criminal complaints. Computational Linguistics in The Netherlands journal, 7, 3-16. https://clinjournal.org/clinj/article/view/65
https://dspace.library.uu.nl/bitstream/handle/1874/356185/01.NERclinjournal.pdf?sequence=1

Overige resultaten

Schraagen, M. P., & Bex, F. J. (2017). Evaluation of named entity recognition in user-submitted police reports. Abstract from CLIN 2017, Leuven, Belgium.
Schraagen, M. P., Dietz, F. M., van Koppen, J. M., & Zervanou, K. (2017). Modernizing historical Dutch: the UU system. Poster session presented at CLIN 2017, Leuven, Belgium.
https://dspace.library.uu.nl/bitstream/handle/1874/356085/clin_poster.pdf?sequence=1
Schraagen, M. P., Dietz, F. M., van Koppen, J. M., van Engeland, J., & van de Poppe, C. J. (2017). Language Sciences Day: Language Dynamics in the Dutch Golden Age: linguistic and socio-cultural aspects of intra-author variation. Poster session presented at Language Science Day, Utrecht University, Utrecht, Netherlands.
https://dspace.library.uu.nl/bitstream/handle/1874/356084/languagesciencesday_poster.pdf?sequence=1

2016

Wetenschappelijke publicaties

Schraagen, M. P., & van Miert, D. K. W. (2016). Author attribution on paragraph level using simulated annealing. In Proceedings of Benelearn 2016
https://dspace.library.uu.nl/bitstream/handle/1874/356257/Benelearn_2016_paper_44.pdf?sequence=1
Schraagen, M. P. (2016). Towards a dynamic application of distributional semantics. In Proceedings of the ESSLLI Workshop on Distributional Semantics and Linguistic Theory
https://dspace.library.uu.nl/bitstream/handle/1874/356745/Schraagen_DSALT_dynamic_ds.pdf?sequence=1
Schraagen, M. P. (2016). Folktale similarity based on ontological abstraction. In V. B. Mititelu, C. Forăscu, C. Fellbaum, & P. Vossen (Eds.), Proceedings of the Eighth Global WordNet Conference (pp. 352-359)
https://dspace.library.uu.nl/bitstream/handle/1874/356256/Schraagen_Folktales_2016.pdf?sequence=1

Overige resultaten

Dietz, F. M., van Koppen, J. M., van Engeland, J., van de Poppe, C. J., & Schraagen, M. P. (2016). Language Dynamics in the Dutch Golden Age: Linguistic and socio-cultural aspects of intra-author variation. Poster session presented at Digital Humanities Community Event, Utrecht, Netherlands.

2015

Wetenschappelijke publicaties

Bloothooft, G., & Schraagen, M. P. (2015). Learning Name Variants from Inexact High-Confidence Matches. In G. Bloothooft, P. Christen, K. Mandemakers, & M. Schraagen (Eds.), Population Reconstruction (pp. 61-83). Springer. https://doi.org/10.1007/978-3-319-19884-2_4
Bloothooft, G., Schraagen, M. P., Mandemakers, K., & Christen, P. (Eds.) (2015). Population reconstruction. Springer. https://doi.org/10.1007/978-3-319-19884-2

2014

Wetenschappelijke publicaties

Schraagen, M., & Kosters, W. (2014). Record linkage using graph consistency. In 10th International Conference on Machine Learning and Data Mining https://doi.org/10.1007/978-3-319-08979-9_36
Bloothooft, G., & Schraagen, M. (2014). Learning name variants from true person resolution. In Proc. of the Int. workshop Population Reconstruction, Amsterdam http://socialhistory.org/sites/default/files/docs/bloothooft_schraagen_-_name_variants_0.pdf

2013

Wetenschappelijke publicaties

Schraagen, M., & Huijsmans, D. (2013). Comparison between historical population archives and decentralized databases. In 7th Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities (pp. 20-28)
van den Heuvel, H., Mertens, J. P., Bloothooft, G., & Schraagen, M. P. (2013). Resources developed in the Autonomata projects. In P. Spyns, & J. Odijk (Eds.), Essential Speech and Language Technology for Dutch. Results by the STEVIN-programme (pp. 71-78). Springer. https://doi.org/10.1007/978-3-642-30910-6_4
Reveil, B., Mertens, J. P., Bloothooft, G., & Schraagen, M. (2013). Lexical Modeling for Proper name Recognition in Autonomata TOO. In P. Spyns, & J. Odijk (Eds.), Essential Speech and Language Technology for Dutch. Results by the STEVIN-programme (pp. 251-270). Springer.

2012

Wetenschappelijke publicaties

Schraagen, M., & Kosters, W. (2012). Data-driven name reduction for record linkage. In Second International Conference on Innovative Computing Technology (pp. 311-316) https://doi.org/10.1109/intech.2012.6457783

2011

Wetenschappelijke publicaties

Schraagen, M., & Hoogeboom, H. J. (2011). Predicting record linkage potential in a family reconstruction graph. In Proceedings of the 23rd Benelux Conference on Artificial Intelligence (pp. 199-206)
Schraagen, M. (2011). Complete coverage for approximate string matching in record linkage using bit vectors. In 23rd IEEE International Conference on Tools with Artificial Intelligence (pp. 740-747) https://doi.org/10.1109/ICTAI.2011.116
Bloothooft, G., & Schraagen, M. P. (2011). Name fashion dynamics and social class. In Proceedings International Conference of Onomastic Sciences
https://dspace.library.uu.nl/bitstream/handle/1874/355635/ICOS2011_Name_fashion_dynamics_Bloothooft_Schraagen.pdf?sequence=1
Schraagen, M. P., & Bloothooft, G. (2011). A qualitative evaluation of phoneme-to-phoneme technology. In Proceedings Interspeech (Florence)

2010

Wetenschappelijke publicaties

Bloothooft, G., & Schraagen, M. P. (2010). Evaluating repetitions, or how to improve your multilingual ASR system by doing nothing. In Proceedings 7th Linguistic Resources and Evaluation Conference

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