Simon Hengchen
Simon Hengchen
Lecturer, University of Geneva //
Verified email at - Homepage
Cited by
Cited by
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
D Schlechtweg, B McGillivray, S Hengchen, H Dubossarsky, ...
arXiv preprint arXiv:2007.11464, 2020
Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change
H Dubossarsky, S Hengchen, N Tahmasebi, D Schlechtweg
arXiv preprint arXiv:1906.01688, 2019
Quantifying the impact of dirty OCR on historical text analysis: Eighteenth Century Collections Online as a case study
MJ Hill, S Hengchen
Digital Scholarship in the Humanities 34 (4), 825-843, 2019
GASC: Genre-Aware Semantic Change for Ancient Greek
V Perrone, M Palma, S Hengchen, A Vatri, JQ Smith, B McGillivray
The 1st International Workshop on Computational Approaches to Historical …, 2019
From the paft to the fiiture: a fully automatic NMT and word embeddings method for OCR post-correction
M Hämäläinen, S Hengchen
arXiv preprint arXiv:1910.05535, 2019
A computational approach to lexical polysemy in Ancient Greek
B McGillivray, S Hengchen, V Lähteenoja, M Palma, A Vatri
Digital Scholarship in the Humanities 34 (4), 893-907, 2019
DWUG: A large resource of diachronic word usage graphs in four languages
D Schlechtweg, N Tahmasebi, S Hengchen, H Dubossarsky, ...
arXiv preprint arXiv:2104.08540, 2021
Computational approaches to semantic change
N Tahmasebi, L Borin, A Jatowt, Y Xu, S Hengchen
BoD–Books on Demand, 2021
Challenges for computational lexical semantic change
S Hengchen, N Tahmasebi, D Schlechtweg, H Dubossarsky
Computational approaches to semantic change 6, 341, 2021
Topic modelling discourse dynamics in historical newspapers
J Marjanen, E Zosa, S Hengchen, L Pivovarova, M Tolonen
arXiv preprint arXiv:2011.10428, 2020
An unsupervised method for OCR post-correction and spelling normalisation for Finnish
Q Duong, M Hämäläinen, S Hengchen
arXiv preprint arXiv:2011.03502, 2020
The challenges and prospects of the intersection of humanities and data science: A White Paper from The Alan Turing Institute
B McGillivray, B Alex, S Ames, G Armstrong, D Beavan, A Ciula, ...
Alan Turing Institute, 2020
A data-driven approach to the changing vocabulary of the ‘nation’ in English, Dutch, Swedish and Finnish newspapers, 1750-1950
S Hengchen, R Ros, J Marjanen
In Proceedings of the Digital Humanities (DH) conference, 2019
A data-driven approach to studying changing vocabularies in historical newspaper collections
S Hengchen, R Ros, J Marjanen, M Tolonen
Digital Scholarship in the Humanities 36 (Supplement_2), ii109-ii126, 2021
Semantic Enrichment of a Multilingual Archive with Linked Open Data
M De Wilde, S Hengchen
Digital Humanities Quarterly 11 (4), 2015
Exploring archives with probabilistic models: Topic modelling for the valorisation of digitised archives of the european commission
S Hengchen, M Coeckelbergs, S Van Hooland, R Verborgh, T Steiner
2016 IEEE International Conference on Big Data (Big Data), 3245-3249, 2016
When Does it Mean? Detecting Semantic Change in Historical Texts
S Hengchen
Université libre de Bruxelles, 2017
Introduction aux humanités numériques: méthodes et pratiques: sciences humaines et sociales
S Van Hooland, F Gillet, S Hengchen, M De Wilde
De Boeck Université, 2016
L'extraction d'entités nommées: une opportunité pour le secteur culturel?
S Hengchen, S Van Hooland, R Verborgh, M De Wilde
I2D – Information, données & documents, 2015
A collection of Swedish diachronic word embedding models trained on historical newspaper data
S Hengchen, N Tahmasebi
Journal of open humanities data 7, 2021
The system can't perform the operation now. Try again later.
Articles 1–20