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.
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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.