A logic programming framework infers high-level temporal events from timestamped observations via rules for event conditions and repairs for consistency, achieving polynomial data complexity under restrictions and aligning with expert views on lung cancer data.
However, we must also argue that there is not e ∈T ℓ′ × (R(d))that could block such an extension
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Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications
A logic programming framework infers high-level temporal events from timestamped observations via rules for event conditions and repairs for consistency, achieving polynomial data complexity under restrictions and aligning with expert views on lung cancer data.