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Towards Interactive Causal Relation Discovery Driven by an Ontology

Abstract : 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.
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Contributor : Mélanie Munch <>
Submitted on : Tuesday, July 16, 2019 - 9:24:39 AM
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  • HAL Id : hal-02184398, version 1


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⟩



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