SDC, Data Science and Knowledge

Florence le Ber

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Dr. Engineer, HDR in computer sciences

Ecole Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES) : national engineering school of environmental hydraulics

Director of the research departement of ENGEES


E-mail: florence.leber at engees.unistra.fr

Web (ENGEES) : http://engees.unistra.fr/~fleber/ (french)

Phone: 33 3 88 24 82 30


Current and recent Projects

  • SmartFCA (2022-25) : Formal Concept Analysis:A Smart Tool for Analyzing Complex Data - Funding: ANR - in collaboration with LIRMM (leader, Montpellier), LORIA (Nancy), IRISA (Rennes), L3I (La Rochelle), CIRAD, Infologic.
  • MoS-T (2021-25) : Mining and visualizing spatio-temporal patterns inside big graphs - Funding: ANR JCJC (leader Aurélie Leborgne) - in collaboration with Institut Pascal (Le Puy-en-Velay) -- PhD Student: Assaad Zeghina
  • PARADISE (2021-24) : Mediaval pharmacopeia for designing tomorrow medicine - Funding: CNRS MITI - in collaboration with ARCHIMEDE, BSC, Herbier de Strasbourg -- PhD Student: Karim El Haff
  • Organizing chair with Agnès Braud of ICFCA 2021, June 29-July 2 2021 in Strasbourg
  • co-chairing the Int. Conference on Formal Concept Analysis, ICFCA 2019, Frankfurt, June 25-28 2019
  • AFB (2019-2020) : A tool for extracting temporal patterns of water quality status changes (leader Corinne Grac, LIVE)
  • CS ENGEES (2019-2020) : AdQeau - Analysing water quality changes (with Pierre Gançarski)
  • CS ENGEES (2016-2018) : Automatic recognition of sketch maps (leader Carine Heitz, Geste)
  • API ICube SEMNET (2017-2018) : Sensor Networks for Smart Factories
  • ONEMA (2015-2016) : Temporal data mining of national data on water courses (leader Corinne Grac, LIVE)
  • ANR FRESQUEAU (2011-2015) : Data mining for assessing and monitoring the hydrobiological quality of water streams (leader Florence Le Ber)
  • AERM project Gerihco (2010-2013 / 2015-2019) : Interdisciplinay approach to understand the muddy flood risk (leader Anne Rozan, Geste)


Teaching

  • Data Mining (master "Environmental Geography ")
  • Description logics (master "Computer sciences")


Expertise

  • Member of an ANR committee (appel générique) (2022)
  • Member of the CSS 5 IRD scientific committee (2021-2026)
  • Member of ANR/AFD Challenge IA-Biodiv scientific committee (2019)
  • Member of INRA CEI -- Commission d'évaluation des ingénieurs (2013-2018)
  • Member of Conseil Scientifique du bassin Rhin-Meuse (2013-2021)


Previous labs

  • LHYGES (2009 - 2012)
  • CEVH (2003 - 2008)
  • LORIA INRIA, équipe Orpailleur (2000 - 2002)
  • INRA Nancy, LIAB (1991 - 1999)


Recent Publications

A. Ouzerdine , A. Braud, X. Dolques, M. Huchard , F. Le Ber. Adjusting the exploration flow in Relational Concept Analysis -- An experience on a watercourse quality dataset. Advances in Knowledge Discovery and Management, Rakia JAZIRI (Eds.), Springer, 2022.

A. Braud, X. Dolques, A. Gutierrez , M. Huchard , P. Keip , F. Le Ber, P. Martin , C. Nica, P. Silvie. Dealing with Large Volumes of Complex Relational Data using RCA. CDA_FCA'2020, Rokia Missaoui, Léonard Kwuida, Talel Abdessalem (Eds.), Springer, 2022.

C. Grac, X. Dolques, A. Braud, M. Trémolières, J.-N. Beisel, F. Le Ber Mining the sequential patterns of water quality preceding the biological status of waterbodies Ecological Indicators, Elsevier, 2021, 130, ⟨10.1016/j.ecolind.2021.108070⟩

C. Nica, A. Braud, F. Le Ber. RCA-Seq: An original approach for enhancing the analysis of sequential data based on hierarchies of multilevel closed partially-ordered patterns. Discrete Applied Mathematics, Volume 273, 15 February 2020, pp. 232-251

A. Braud, X. Dolques, M. Huchard, F. Le Ber. Generalization effect of quantifiers in a classification based on relational concept analysis. Knowledge-Based Systems, Volume 160, 15 November 2018, pp. 119-135

F. Le Ber, X. Dolques, L. Martin, A. Mille, M. Benoît Raisonner à partir de cas d’allocation dans des parcelles agricoles RIA - Revue d'Intelligence Artificielle, 2017, 2017 (6), pp. 681-707

X. Dolques, F. Le Ber, M. Huchard, C. Grac. Performance-friendly rule extraction in large water data-sets with AOC posets and relational concept analysis. International Journal of General Systems, Taylor & Francis, 2016, 45 (2), pp. 187-210.

J. Wiederkehr, C. Grac, B. Fontan, F. Labat, F. Le Ber, M. Trémolières. Experimental study of the uncertainty of the intrasubstrate variability on two French index metrics based on macroinvertebrates. Hydrobiologia, Springer, 2016, 779(1), pp. 59–73.


... others here : http://hal.archives-ouvertes.fr/...