TY - GEN
T1 - The Use of Classification in Automated Mathematical Concept Formation
AU - Colton, S.
AU - Cresswell, S.
AU - Bundy, Alan
PY - 1997
Y1 - 1997
N2 - Concept formation programs aim to produce a high yield of concepts which are considered interesting. One intelligent way to do this is to base a new concept on one or more concepts which are already known to be interesting. This requires a concrete notion of the ‘interestingness’ of a particular concept. Restricting the concepts formed to mathematical definitions in finite group theory, we derive three measures of the interestingness of a concept. These measures are based on how much the concept improves a classification of finite groups.
AB - Concept formation programs aim to produce a high yield of concepts which are considered interesting. One intelligent way to do this is to base a new concept on one or more concepts which are already known to be interesting. This requires a concrete notion of the ‘interestingness’ of a particular concept. Restricting the concepts formed to mathematical definitions in finite group theory, we derive three measures of the interestingness of a concept. These measures are based on how much the concept improves a classification of finite groups.
M3 - Conference contribution
SN - 9780907330271
BT - Proceedings of SimCat 1997: An Interdisciplinary Workshop on Similarity and Categorisation, November 28-30, 1997, Edinburgh University
PB - Department of Artificical Intelligence, Edinburgh University
ER -