Collaborative Group Decision for knowledge acquisition in agriculture using AI techniques

Ficha técnica

Título:Collaborative Group Decision for knowledge acquisition in agriculture using AI techniques
Código:22-STIC-01
Duración:1 Marzo 2022 - 1 Marzo 2024
Dirección:
Co-Dirección:
Grupo responsable:Responsable por Argentina: Leandro Antonelli - Responsable por Colombia: Cesar Collazos - Responsable por Francia: Pascale Zarate
Sitio web:
Financiador:STIC AmSud
Monto:
Participantes (del LIFIA)Alejandro Fernandez, Claudia Pons, Diego Torres, Leandro Antonelli, Matías Urbieta

Resumen

Knowledge acquisition is a key step to understand the domain in order to make proposals to obtain better results. Natural Language Processing tools in combination with Machine Learning (both from the Artificial Intelligence field) can be used to analyze the narrative descriptions captured, in order to obtain an ontology representation of the knowledge acquired. Considering the agricultural context and the use of technology, knowledge acquisition should be done with tools that suit the characteristics of the stakeholders and provide the accuracy of knowledge description needed in a technological environment. We consider three aspects to be taken into account. Collaborative Knowledge Management (CKM) is considered as a process of collective resolution of problems where it is useful to memorize the process of making collective decisions and to structure the group interactions to facilitate problem solving and sharing of ideas. Then scenarios are widely used to capture the knowledge from the stakeholders. Finally, conflict resolution is a step to be considered in knowledge acquisition. It is crucial making the group decision process interactive, iterative, collaborative and participatory. Thus, a multi-criteria decision support system arises as a tool to support this process.

Publicaciones

Leutwyler, Nicolas, Lezoche, Mario, Panetto, Hervé and Torres, Diego, "Software genérico para benchmarking del Análisis Conceptual Formal: Integración de Orange3," Electronic Journal of SADIO (EJS), vol. 22, pp. 28-40, ago.. 2023. 

Christian Ezequiel Bracco, Lucas Ezequiel Cuevas and Diego Torres: Semantic Annotation in Collaborative Document Transcription: A Gamified Citizen Science Approach. In: Culture and Computing. (2023), 491--508 

Becas y pasantías

Tesis y trabajos finales de carrera

Nicolás Leutwyler (Doctorado). Formal methods for knowledge extraction and reuse from heterogeneous sources: applications to the semantic interoperability of distributed architectures. Doctorado de la Universidad de Lorena y Doctorado de la UNQ. Dirigido por Diego Torres, Mario Lezoche, Hervé Panetto. Duración: 24/11/2021 - en curso

Mariano Ferreirone (Doctorado). Intelligent formal analysis of heterogeneous data for semantic web. Doctorado Université de Lorena. Dirigido por Diego Torres, Mario Lezcohe, Hervé Panetto. Duración: 28/2/2022 - en curso

Diego Lopez Yse (Master). Drug Repurposing utilizando Embeddings sobre Grafos de Conocimiento. MAESTRÍA EN EXPLOTACIÓN DE DATOS Y GESTIÓN DEL CONOCIMIENTO. Dirigido por Diego Torres. Co-Dirigido por Ariel Gulisiano. Duración: 14/5/2022 - en curso

Juan Diego Bravo Guevara y Elmer Jose Muñoz Zuñiga (Tesina de grado). Patrones de Diseño de Interfaces Web Personalizables Para Mejorar la Solución de Tareas Complejas en un Sistema de Servicio al Cliente en Línea Basado en Chatbots. Universidad del Cauca Facultad de Ingeniería Electrónica y Telecomunicaciones. Dirigido por Cesar Collazos. Co-Dirigido por Diego Torres. Duración: 27/10/2022 - en curso