Rule invocation mechanism for inductive learning engine

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395 51, 395 77, G06F 1518

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052221970

ABSTRACT:
A rule invocation mechanism in an inductive learning engine employing symbolic rules for characterizing a sequence of time-related events. The rules to be tested as hypotheses against new events in the sequence are ranked according to their information content or "quality" value. The efficiency of the rule-to-event pattern matching process for characterizing the new events is increased by not testing a hypothesis if a much better hypothesis already exists. Those hypotheses that characterize events in the sequence are tagged to the event.

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