[Defended thesis] Priscilla Keip: Selecting pesticidal plants for animal and plant health in Africa using exploratory conceptual navigation

Priscilla is one of the #DigitAg co-funded PhDs

Priscilla defended her thesis on 16th December 2021 at 9 AM @ Université de Montpellier – Campus Saint-Priest, LIRMM, 161, rue Ada, Bâtiment 4, Ground floor, salle de Séminaires (main entrance)

Selecting pesticidal plants for animal and plant health in Africa using exploratory conceptual navigation

  • Start Date: November 2018
  • University: Montpellier University of Excellence
  • PhD School: I2S – Information, Structures, Systèmes
  • Field(s): Computer Science
  • Doctoral Thesis Advisor: Marianne Huchard, Université de Montpellier, LIRMM
  • Co-supervisors : Marianne Huchard, Université de Montpellier, LIRMM, Pierre Martin et Pierre Silvie, Cirad, Aida
  • Funding: #DigitAg – Cirad
  • #DigitAg: Axis 5 – Challenges : cross-cutting subject

Keywords: pesticides plants – Data Mining – Data exploration – Data navigation – Visualization – human-machine interactio

Abstract: Cirad develops several knowledge bases, including PPAf (project Knomana 2017-2018, métaprogramme Glofoods) which gathers usages of plants for animal and vegetal health. The gathered knowledge is useful for identifying alternatives to chemical pesticides and to chemical antibiotics for culture and breeding. As many different knowledge kinds are involved (taxonomy, geography, reliability of information sources, etc.), the knowledge visualization and exploration by end users (farmers, scientists, decision-makers, etc.) is complex. The thesis aims to elaborate a general methodology, theoretical tools and a prototype tool to answer the following questions: – Which is the best support for integrating and representing PPAf knowledge? – Which data mining techniques will be adapted to analyze the existing knowledge (decision trees, association rules, formal concept analysis)? – Which human-machine interaction method would allow different users with different profiles to express queries and analyze knowledge on-the-fly according the navigation context?

Contact: priscilla.keip [AT] cirad.fr​

Communications /Publications

Download the thesis manuscript

Braud A., Dolques X., Gutierrez A., Huchard M., Keip P., Le Ber F., Martin P., Nica C. and Silvie P (2020),Dealing with Large Volumes of Complex Relational Data using RCA, Complex Data Analytics with Formal Concept Analysis

Papers at international conferences

  • Silvie P.J., Martin P., Huchard M., Keip P., Gutierrez A., Sarter S. (2021) Prototyping a knowledge-based system to identify botanical extracts for plant health in sub-saharan africa, Plants
  • Keip P., Ferre S., Gutierrez A., Huchard M., Silvie S., Martin P (2020), Practical Comparison of FCA Extensions to Model Indeterminate Value of Ternary Data, The 15th International Conference on Concept Lattices and Their Applications (CLA 2020). Tallinn, Estonia, 29-1/06-07/2020 –  https://agritrop.cirad.fr/596562/
  • Mahrach L., Gutierrez A., Huchard M., Keip P., Silvie P., Martin P (2020), Extraction of association rules from knowledge on plants with pesticidal and antibiotic effect classified by FCA for the One-Health initiative, JOBIM 2020
  • Keip Priscilla, Ouzerdine Amirouche, Huchard Marianne, Silvie Pierre, Martin Pierre (2019), Navigation conceptuelle dans une base de connaissances sur l’usage des plantes en santé animale et végétale, CORIA 2019, 16th French Information Retrieval Conference – https://agritrop.cirad.fr/593472/1/Keip_et_al_2019a.pdf
  • Bazin Alexandre, Carbonnel Jessie, Huchard Marianne, Kahn Giacomo, Keip Priscilla, Ouzerdine Amirouche(2019), On-demand Relational Concept Analysis, IFCA 2019 – https://arxiv.org/abs/1803.07847
  • Keip Priscilla, Gutierrez Alain, Huchard Marianne, Le Ber Florence, Sarter Samira, Silvie Pierre, Martin Pierre, Effects of input data formalisation in relational concept analysis for a data model with a ternary relation, International Conference on Formal Concept Analysis (ICFCA 2019) – https://link.springer.com/chapter/10.1007%2F978-3-030-21462-3_13