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Journal Articles Frontiers in Artificial Intelligence Year : 2022

Structuring ontologies from natural language for collaborative scenario modeling in agri-food systems

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Abstract

Prospective studies require discussing and collaborating with the stakeholders to create scenarios of the possible evolution of the studied value-chain. However, stakeholders do not always use the same words when referring to one idea. Constructing an ontology and homogenizing vocabularies is thus crucial to identify key variables, which serve in the construction of the needed scenarios. Nevertheless, it is a very complex and time-consuming task. In this paper we present the method we used to manually build ontologies adapted to the needs of two complementary system-analysis models (namely the “Godet” and the “MyChoice” models), starting from interviews of the agri-food system's stakeholders. The objective of the paper is to explore whether and how prospective studies may have to gain from complementing the methodologies used (here Godet) with formal approaches from other disciplines, such as knowledge engineering (here MyChoice), which is usually not the case currently.
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Dates and versions

hal-03942429 , version 1 (17-01-2023)

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Attribution - CC BY 4.0

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Romy Lynn Chaib, Catherine Macombe, Rallou Thomopoulos. Structuring ontologies from natural language for collaborative scenario modeling in agri-food systems. Frontiers in Artificial Intelligence, 2022, ⟨10.3389/frai.2022.1056989⟩. ⟨hal-03942429⟩
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