Présentation des thèmes de recherche

Computational Linguistics, Natural Language Processing, Information Extraction, Named-Entity Recognition, Topic Modelling, Machine Translation

Lien vers un site externe

http://homepages.ulb.ac.be/~shengche

Centre(s) de recherche

Recherche en Sciences de l'information et de la communication (ReSIC)

Publication(s) récente(s)

Hengchen, S. (2017). Detecting Semantic Change in Historical Texts. Publication présentée à la conférence Hume, Rousseau, History and Method (2017-12-07: Helsinki).

Hengchen, S. (2017). When Does it Mean?: Detecting Semantic Change in Historical Texts (Thèse doctorale non-publiée). Université libre de Bruxelles, Faculté de Lettres, Traduction et Communication - Information et communication, Bruxelles.

McGillivray, B., & Hengchen, S. (2017, novembre 02). Code for the Hartlib Papers. doi:10.5281/zenodo.1040682

Hengchen, S. (2017). Detecting Semantic Change in Historical Text: Case Study on Flemish socialist newspapers. Publication présentée à la conférence Language Technology Lab (Cambridge).

Van Hooland, S., Coeckelbergs, M., Hengchen, S., & Rizza, E. (2017). Scrambling for Metadata: Using Topic Modeling and Word2Vec to Explore the Archives of the European Commission. Publication présentée à la conférence Digital approaches towards serial publications (18th–20th centuries).

Verbruggen, C., Hengchen, S., Zere, T., D'Haeninck, T., & Daems, J. (2017). Workers of the World? A Digital Approach Towards the International Scope of Belgian Socialist Newspapers, 1885-1940. Publication présentée à la conférence Digital approaches towards serial publications (18th–20th centuries).

D'Haeninck, T., Hengchen, S., & Verbruggen, C. (2017). A Genealogy of Causes: Recognizing Social Reform Topics in 19th-century Congress Series. Publication présentée à la conférence Digital approaches towards serial publications (18th–20th centuries) (Brussels).

Hengchen, S. (2017). When does it mean?: Detecting semantic change in historical texts. Publication présentée à la conférence Digital Humanities at Oxford Summer School (Oxford).

Chardonnens, A., & Hengchen, S. (2017, mars 15). Text Mining for User Query Analysis: A 5-Step Method for Cultural Heritage Institutions. Proceedings of the 15th International Symposium on Information Science (ISI 2017) ; Berlin, Germany, 13th—15th March 2017: Everything Changes, Everything Stays the Same? Understanding Information Spaces (pp. 177-189). M. Gäde / V. Trkulja / V. Petras (Eds.).

De Wilde, M., & Hengchen, S. (2017). Semantic Enrichment of a Multilingual Archive with Linked Open Data. Digital Humanities Quarterly, 11(4).