ENEXA
Financiado
Efficient Explainable Learning on Knowledge Graphs
Explainable Artificial Intelligence (AI) is key to achieving a human-centred and ethical development of digital and industrial solutions. ENEXA builds upon novel and promising results in knowledge representation and machine learni...
Explainable Artificial Intelligence (AI) is key to achieving a human-centred and ethical development of digital and industrial solutions. ENEXA builds upon novel and promising results in knowledge representation and machine learning to develop scalable, transparent and explainable machine learning algorithms for knowledge graphs. The project focuses on knowledge graphs because of their critical role as enabler of new solutions across domains and industries in Europe. Some of the existing machine learning approaches for knowledge graphs are known to already provide guarantees with respect to their completeness and correctness. However, they are still impossible or impractical to deploy on real-world data due to the scale, incompleteness and inconsistency of knowledge graphs in the wild. We devise approaches that maintain formal guarantees pertaining to completeness and correctness while being able to exploit different representations of knowledge graphs in a concurrent fashion. With our new methods, we plan to achieve significant advances in the efficiency and scalability of machine learning, especially on knowledge graphs. A supplementary innovation of ENEXA lies in its approach to explainability. Here, we focus on devising human-centred explainability techniques based on the concept of co-construction, where human and machine enter a conversation to jointly produce human-understandable explanations. Three use cases on business software services, geospatial intelligence and data-driven brand communication have been chosen to apply and validate this new approach. Given their expected growth rates, these sectors will play a major role in future European data value chains.
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Duración del proyecto: 35 meses
Fecha Inicio: 2022-10-01
Fecha Fin: 2025-09-30
Fecha Fin: 2025-09-30
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-10-01
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
HORIZON-CL4-2021-HUMAN-01-26:
Workforce skills for industry 5.0 (RIA)
Cerrada
hace 3 años
Presupuesto
El presupuesto total del proyecto asciende a
4M€
Líder del proyecto
UNIVERSITAET PADERBORN
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5