Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 14th June 2025, 06:29:53pm WEST
Session Chair: Gimena del Rio Riande, Consejo Nacional de Investigaciones Científicas y Técnicas
Location:B309 (TB)
60 places
Presentations
Can African policies support community-led governance over cultural property in the age of artificial intelligence?
Harriet Deacon1, Leonce Ki2, Freda Owusu3, Avril Joffe4, Bhupesh Mishra1, Kevin Pimbblet1, Mathilde Pavis3
1University of Hull / DAIM, United Kingdom; 2Universite Nazi Boni, Burkina Faso; 3Independent scholar and consultant; 4University of the Witwatersrand, South Africa
Many African policies position both digital /AI technologies and cultural industries as engines of sustainable development, but use of AI can also undermine artist livelihoods. The paper will consider how African policy frameworks could support communities in managing, protecting and promoting their digital cultural information in the age of AI.
Du repérage à l’analyse : un modèle NER pour l’analyse des entités nommées dans les textes littéraires
Perrine MAUREL1, Arthur AMALVY2, Vincent LABATUT2, Motasem ALRAHABI1
1Sorbonne Université; 2Université d’Avignon
Cette étude présente la création d’un corpus de romans du 19ᵉ siècle annotés en entités nommées dans leur intégralité, et l’élaboration d’un modèle de reconnaissance d’entités nommées adapté à de tels longs textes littéraires, et disponible librement en ligne. Nous évaluons ses performances, démontrant sa précision et sa robustesse.
The power of context: Random Forest classification of (near) synonyms. A case study in Modern Hindi
Jacek Bąkowski
Institute of Polish Language, Polish Academy of Sciences, Poland
This paper investigates the problem of synonymy in the langugage, namely is a classifier based only on word embeddingsl able to correctly classify synonyms according to their origin.
Although the language used for this analysis is Modern Hindi—significantly underrepresented in contemporary language research—the methodology presented is language-agnostic.
