Abstract: The analysis of large volumes of textual data requires the use of text-mining approaches. They enable to discover knowledge useful for experts of different domains (e.g. Epidemiology, Humanities, etc.). The course will present some approaches in order to deal with heterogenous textual data by focusing on the identification of thematic and spatial information in texts.
Resume: Mathieu Roche is a Senior Research Scientist (PhD, HDR) at CIRAD – TETIS research unit. Currently he is leader of SISO group (i.e. Spatial Information, Modelling, Data Mining, and Knowledge Extraction) at TETIS. Between 2005 and 2013, he has been Associate Professor (Maître de Conférences) at University Montpellier 2, France. Mathieu Roche obtained a PhD in Computer Science from University Paris 11 (Orsay) in 2004. He defended his HDR (Habilitation à Diriger des Recherches – Accreditation to supervise research) in 2011. At LIRMM, he was co-leader (2010-2012) and leader (2012-2013) of TEXT group. At the University Montpellier 2, he was in charge of the Master “Intégration de Compétences” (2008-2011). Mathieu Roche led several academic and industrial projects in text-mining (e.g. Songes – FEDER, Animitex – CNRS, Resens – CNRS, Senterritoire – MSH-M). He has supervised 13 PhD students and he has been co-chair of 13 conferences and workshops. Mathieu Roche published more than 180 papers in conferences and journals.