| SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection D Schlechtweg, B McGillivray, S Hengchen, H Dubossarsky, ... arXiv preprint arXiv:2007.11464, 2020 | 138 | 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 | 82 | 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 | 49 | 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 | 34 | 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 | 28 | 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 | 22 | 2019 |
| Semantic Enrichment of a Multilingual Archive with Linked Open Data M De Wilde, S Hengchen Digital Humanities Quarterly 11 (4), 2015 | 18 | 2015 |
| 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 | 16 | 2019 |
| 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 | 15 | 2016 |
| Challenges for computational lexical semantic change S Hengchen, N Tahmasebi, D Schlechtweg, H Dubossarsky Computational approaches to semantic change 6, 341, 2021 | 12 | 2021 |
| When Does it Mean? Detecting Semantic Change in Historical Texts S Hengchen Université libre de Bruxelles, 2017 | 11 | 2017 |
| 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 | 11 | 2015 |
| An unsupervised method for OCR post-correction and spelling normalisation for Finnish Q Duong, M Hämäläinen, S Hengchen arXiv preprint arXiv:2011.03502, 2020 | 10 | 2020 |
| 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 | 9 | 2021 |
| Topic modelling discourse dynamics in historical newspapers J Marjanen, E Zosa, S Hengchen, L Pivovarova, M Tolonen arXiv preprint arXiv:2011.10428, 2020 | 8 | 2020 |
| Computational approaches to semantic change N Tahmasebi, L Borin, A Jatowt, Y Xu, S Hengchen BoD–Books on Demand, 2021 | 7 | 2021 |
| 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, ... | 6 | 2020 |
| 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 | 5 | 2021 |
| A collection of swedish diachronic word embedding models trained on historical newspaper data S Hengchen, N Tahmasebi Journal of Open Humanities Data 7, 2021 | 5 | 2021 |
| The Strengths and Pitfalls of Large-Scale Text Mining for Literary Studies N Tahmasebi, S Hengchen Samlaren: Tidskrift för forskning om svensk och annan nordisk litteratur 140 …, 2019 | 5 | 2019 |
Nina TahmasebiAssociate Professor in NLP, University of GothenburgVerified email at gu.se
