Towards Interactive Causal Relation Discovery Driven by an Ontology

Mélanie Munch (1) , Juliette Dibie-Barthelemy (1) , Pierre-Henri Wuillemin (2) , Cristina Manfredotti (1)

1 MIA-Paris - Mathématiques et Informatique Appliquées
2 DECISION

Discovering causal relations in a knowledge base represents nowadays a challenging issue, as it gives a brand new way of understanding complex domains. In this paper, we present a method to combine an ontology with a probabilistic rela-tional model (PRM), in order to help a user to check his/her assumption on causal relations between data and to discover new relationships. This assumption is important as it guides the PRM construction and provide a learning under causal constraints.

Domaines: Intelligence artificielle [cs.AI]

Mélanie Munch, Juliette Dibie-Barthelemy, Pierre-Henri Wuillemin, Cristina Manfredotti. Towards Interactive Causal Relation Discovery Driven by an Ontology. FLAIRS 32, May 2019, Sarasota, United States. ⟨hal-02184398⟩