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Poumay Judicaël

HEC Liège : UER > UER Opérations : Systèmes d'information de gestion

HEC Liège Research: Business Analytics & Supply Chain Mgmt

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Main Referenced Co-authors
Ittoo, Ashwin  (3)
Main Referenced Keywords
Computer Science - Computation and Language (1); Computer Science - Information Retrieval (1); Computer Science - Learning (1); hierarchical topic (1); topic model (1);
Main Referenced Disciplines
Computer science (6)
Quantitative methods in economics & management (1)

Publications (total 7)

The most downloaded
53 downloads
Poumay, J., & Ittoo, A. (2022). Using meaning instead of words to track topics. Natural Language Processing and Information Systems. https://hdl.handle.net/2268/292154

The most cited

1 citations (Scopus®)

Poumay, J., & Ittoo, A. (2021). A Comprehensive Comparison of Word Embeddings in Event & Entity Coréférence Resolution. In Findings of ACL: EMNLP 2021. Punta Cana, Dominican Republic: Association for Computational Linguistics. doi:10.18653/v1/2021.findings-emnlp.235 https://hdl.handle.net/2268/267116

Poumay, J. (2023). NLP Methods for Weak Signals Detection from Unstructured Text [Doctoral thesis, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/308241

Poumay, J. (09 September 2023). Word Embeddings in Coreference Resolution [Paper presentation]. NLP Seminar, Groningen, Netherlands.

Poumay, J. (26 May 2023). Tree Based Gibbs Sampling for Hierarchical Topic Model [Paper presentation]. The 37th annual conference of the Belgian Operational Research Society (ORBEL 37), Liege, Belgium.

Poumay, J. (2023). Word embeddings et la topologie du language [Paper presentation]. Lunch talk : UER Operations, Liège, Belgium.

Poumay, J., & Ittoo, A. (2022). Using meaning instead of words to track topics. Natural Language Processing and Information Systems.
Peer reviewed

Poumay, J., & Ittoo, A. (2021). A Comprehensive Comparison of Word Embeddings in Event & Entity Coréférence Resolution. In Findings of ACL: EMNLP 2021. Punta Cana, Dominican Republic: Association for Computational Linguistics. doi:10.18653/v1/2021.findings-emnlp.235
Peer reviewed

Poumay, J., & Ittoo, A. (2021). HTMOT : Hierarchical Topic Modelling Over Time (Submitted to Information Systems Research, April 2022). ORBi-University of Liège. https://orbi.uliege.be/handle/2268/292032.

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