A Case for Numerical Taxonomy in Case-Based Reasoning

Authors:
Luís A. Silva;John A. Campbell;Nicholas Eastaugh;Bernard F. Buxton
Affiliations:
Department of Computer Science, University College London, London, UK WC1E 6BT;Department of Computer Science, University College London, London, UK WC1E 6BT;The Pigmentum Project, Research Laboratory for Archaeology and the History of Art, University of Oxford, Oxford, UK OX1 3QY;Department of Computer Science, University College London, London, UK WC1E 6BT
Venue:
SBIA '08 Proceedings of the 19th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
Year:
2008

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Abstract

There are applications of case-like knowledge where, on the one hand, no obvious best way to structure the material exists, and on the other, the number of cases is not large enough for machine learning to find regularities that can be used for structuring. Numerical taxonomy is proposed as a technique for determining degrees of similarity between cases under these conditions. Its effect is illustrated in a novel application for case-like knowledge: authentication of paintings.