Leveraging Knowledge Graph to design the Machine-Learning Engineering Body-of-Knowledge - IRT SystemX
Communication Dans Un Congrès Année : 2024

Leveraging Knowledge Graph to design the Machine-Learning Engineering Body-of-Knowledge

Juliette Mattioli
Dominique Tachet
  • Fonction : Auteur
Fabien Tschirhart
  • Fonction : Auteur
  • PersonId : 1418025
Henri Sohier
  • Fonction : Auteur
  • PersonId : 1054948
Loic Cantat
  • Fonction : Auteur
  • PersonId : 751231
  • IdHAL : loic-cantat

Résumé

A body of knowledge (BoK) is the complete set of concepts, terms, standards and activities promoting abroad awareness of a field or profession to guide practice or work. This paper presents how knowledge-based artificial intelligence (a.k.a. symbolic AI) could be used to build a body of knowledge (BoK) by first identifying relevant documents and data to capture concepts, standards, best practices, and state-of-the-art; then fusing all knowledge items into a knowledge graph, and finally providing query capacities. The overall process of knowledge collection, storage, and retrieval is implemented to support a trustworthy Machine Learning end-to-end engineering
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Dates et versions

hal-04706669 , version 1 (27-09-2024)

Identifiants

  • HAL Id : hal-04706669 , version 1

Citer

Juliette Mattioli, Dominique Tachet, Fabien Tschirhart, Henri Sohier, Loic Cantat, et al.. Leveraging Knowledge Graph to design the Machine-Learning Engineering Body-of-Knowledge. IEEE International Conference on AI x Science, Technology, and Technology (AIxSET), Sep 2024, Laguna hills, United States. ⟨hal-04706669⟩
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