
Découverte de connaissances et Intelligence Artificielle
Extracting knowledge from the Big Data has become increasingly difficult; as a consequence, Knowledge Organization and Mining (KOM) methods and tools are more and more necessary. In a context of heterogeneous data of unequal quality, Data Science emerges with a collection of new tools dedicated to wrapping, mining, classifying and visualization. A new and vast field of research centered on Knowledge Organization and Mining, with its own and innovative experimentations and assessment methods is emerging at the crossroads of the Semantic Web, the Social Web, Ontologies and Recommender Systems.
La liste non exhaustive des sujets considérés est la suivante: / Topics of interest are the following but not limited to:
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– Hugo Alatrista-Salas, Pontificia Universidad Católica del Perú, Perú – Jérôme Azé, LIRMM, University of Montpellier, France – Nicolas Béchet, Bretagne Sud University, France – Hacene Belhadef, University of Constantine 2, Algérie – Ibrahim Bounhas, Manouba University, Tunisie – Sandra Bringay, LIRMM, Paul-Valéry University, France – Gaoussou Camara, Alioune Diop de Bambey University, Sénégal – Juliette Dibie, AgroP- ClemearisTech, Paris, France – Mokhtar Sellami, Université Annaba, Algérie [co-chair KoDAI] – Asma Bouhafs Hafsia, IHEC, Carthage, Tunisie – Patrice Buche, INRA, France – Roberto Interdonato, Cirad, France – Josvah Paul Razafimandimby, U.Fianarantsoa, Madagascar |
– Eric Kergosien, Geriico, University of Lille 3, France
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