An iterative approach to build relevant ontology-aware data-driven models - application to food processes

Abstract : In experimental Life Sciences, simulations are needed in order to extrapolate costly experiments and to design decision-support tools. When extensive mathematical knowledge is not available at the desired scale, expertise and data-driven models can be used as a basis for these simulations. We propose a generic iterative approach to design ontology-aware and relevant data-driven models. It is based upon an ontology to model the domain knowledge, and it uses decision trees as the learning method.
Type de document :
Poster
EFFoST'2012: Annual Meeting "A Lunch Box for Tomorrow: An interactive combination of integrated analysis and specialized knowledge of food", 2012, Montpellier, France. 2012
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00835215
Contributeur : Rallou Thomopoulos <>
Soumis le : mardi 18 juin 2013 - 11:29:32
Dernière modification le : jeudi 11 janvier 2018 - 16:19:58

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  • HAL Id : lirmm-00835215, version 1

Citation

Rallou Thomopoulos, Sébastien Destercke, Brigitte Charnomordic, Joël Abécassis. An iterative approach to build relevant ontology-aware data-driven models - application to food processes. EFFoST'2012: Annual Meeting "A Lunch Box for Tomorrow: An interactive combination of integrated analysis and specialized knowledge of food", 2012, Montpellier, France. 2012. 〈lirmm-00835215〉

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