Knowledge discovery in deep blue
Level 5 - mechanism / opinion, no new human data
Level 5 by design analogy; descriptive technical report and expert case overview without comparative experimental controls.
OpenAlex W1997922645 · doi:10.1145/319382.319396
What was done
The authors describe the system design and knowledge-discovery process used by Deep Blue, focusing on its method of extracting usable knowledge from a database of 700,000 Grandmaster chess games.
What was found
The abstract reports that Deep Blue became the first chess computer to defeat a reigning human world chess champion in a regulation match, supported by extracting knowledge from 700,000 Grandmaster games. No additional quantitative performance metrics are provided in the abstract.
Why it matters
It highlights how large-scale knowledge extraction from expert domain datasets can be applied to complex decision-making systems beyond chess.
Limits
The abstract is truncated and provides no detailed algorithmic descriptions, baseline comparisons, or formal quantitative metrics. As a single-system narrative overview, it lacks experimental evaluation.
Cited by
- supports AI defeated chess champion Garry Kasparov in 1997.