A case for numerical taxonomy in case-based reasoning

Luís A.L. Silva, John A. Campbell, Nicholas Eastaugh, Bernard F. Buxton

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationAdvances in Artificial Intelligence - SBIA 2008 - 19th Brazilian Symposium on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Pages177-186
Number of pages10
ISBN (Print)3540881891, 9783540881896
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event19th Brazilian Symposium on Artificial Intelligence, SBIA 2008 - Salvador, Brazil
Duration: 26 Oct 200830 Oct 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5249 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th Brazilian Symposium on Artificial Intelligence, SBIA 2008
Country/TerritoryBrazil
CitySalvador
Period26/10/0830/10/08

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