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UID:7053-1742810400-1742810400@isdm.umontpellier.fr
SUMMARY:Datalog Fact Explanation Using Group-SAT Solver
DESCRIPTION:Salle des conseils P Raynaud\, au 2ème étage\, du bâtiment 11 dit le château\, 2 Place Pierre Viala Campus La Gaillarde\nSEmantic web SeminAr MontpEllier\nPierre BISQUERT (INRAE IATE) \nAbstract: One of the major benefits of symbolic AI is explainability. When new knowledge is obtained via a reasoning process\, it is possible to determine precisely the elements of the knowledge base that yield this knowledge. Typically\, one would use a SAT solver to compute the explanations. However\, SAT-solving is computationally expensive\, and as the knowledge base grows\, the time required increases exponentially. \nIn this talk\, we will 1) discuss the notion(s) of explanation of a query in the context of a (Datalog) knowledge base\, then 2) we will present a method to optimise the time used by the SAT solver (by creating a hypergraph representing the grounded knowledge base and pruning the nodes that are not reachable from the fact that we want to explain)\, and finally 3) we will see its implementation in the context of InteGraal\, a tool for reasoning over heterogeneous and federated data sources.
URL:https://isdm.umontpellier.fr/event/datalog-fact-explanation-using-group-sat-solver-2/
CATEGORIES:Séminaire
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