The ANR InSciM project aims to study uncertainty in science through ontological and linguistic modelling of this notion from datasets of articles in different disciplines. The objectives are to propose a linguistic model of the expression of uncertainty in scientific articles, in order to propose a tool to identify and classify these phenomena present in papers in different disciplines in Social Sciences and Humanities (SSH) and in Science, Technology, and Medicine (STM).
The objective of the EMONTAL project is to propose a methodology to automatically process documentary and archive collections of heterogeneous natures (newspapers, chronicles, administrative documents, reports, etc.) for the purpose of heritage enhancement dedicated to a given socio-historical context. historical context. This is based on the development of textual analyses, which fall within the field of Automatic Language Processing and discourse analysis.
Gutehrlé, N. (2024). Semantic Search in Archive Collections Through Interpretable and Adaptable Relation Extraction About Person and Places. In N. Goharian, N. Tonellotto, Y. He, A. Lipani, G. McDonald, C. Macdonald & I. Ounis (Éd.), Advances in Information Retrieval (p. 315-318). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56069-9_37
Gutehrlé, N., & Atanassova, I. (2023). Comprendre les archives : vers de nouvelles interfaces de recherche reposant sur l’annotation sémantique des documents Understanding Archives : Towards New Research Interfaces Relying on the Semantic Annotation of Documents. CiDE.23 : Document et archivage : pratiques formelles et informelles. https://hal.science/hal-04523110 https://hal.science/hal-04523110
Gutehrlé, N., Doucet, A., & Jatowt, A. (2022). Archive TimeLine Summarization (ATLS): Conceptual Framework for Timeline Generation over Historical Document Collections. Proceedings of the 6th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, 13-23. https://aclanthology.org/2022.latechclfl-1.3 https://aclanthology.org/2022.latechclfl-1.3/
Gutehrlé, N., & Atanassova, I. (2022). Processing the structure of documents: Logical Layout Analysis of historical newspapers in French. Journal of Data Mining & Digital Humanities, NLP4DH. https://doi.org/10.46298/jdmdh.9093 https://jdmdh.episciences.org/9614/pdf
Gutehrlé, N., Harlamov, O., Karimi, F., Wei, H., Jean-Caurant, A., & Pivovarova, L. (2021). SpaceWars: A Web Interface for Exploring the Spatio-temporal Dimensions of WWI Newspaper Reporting. HistoInformatics 2021 – 6th International Workshop on Computational History. https://ceur-ws.org/Vol-2981/paper3.pdf