Fouille de textes et Intelligence Artificielle pour l'agriculture numérique

Roche Mathieu. 2024. Fouille de textes et Intelligence Artificielle pour l'agriculture numérique. . Institut Agro Montpellier, INRAE, CIRAD, AgroParisTech, Agreenium. Montpellier : Institut Agro Montpellier, Résumé, 1 p. Séminaire de l'Ecole Internationale de Recherche d'Agreenium (EIR-A 2024). 13, Montpellier, France, 3 Juin 2024/7 Juin 2024.

Matériel d'accompagnement : 1 diaporama (40 vues)

Résumé : The ability to identify information in textual data is challenging for applications in the agriculture domain (e.g., agroecology, food security, epidemiology surveillance for animal and plant health). In this context, event-based surveillance (EBS) systems integrate textmining and artificial intelligence methods (i.e. language models) to deal with huge amounts of textual data. This talk focuses on the use artificial intelligence and multidisciplinary approaches in order to mine heterogenous data dealing with the agriculture domain. The proposed methods associated with labeled textual datasets are integrated in the main steps of EBS systems: data acquisition, information retrieval (i.e., identification of relevant texts and topics), information extraction in textual content (i.e., locations, dates, themes), information to communicate to end-users.

Mots-clés libres : Artificial intelligence, Text Mining, Language Model, Digital agriculture, Event based-surveillance, Food Security, Agroecology

Agences de financement hors UE : Agence Nationale de la Recherche

Projets sur financement : (FRA) Institut Convergences en Agriculture Numérique

Auteurs et affiliations

• Roche Mathieu, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-3272-8568

Source : Cirad-Agritrop (https://agritrop.cirad.fr/609630/)

Métriques

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