Measuring the applicability of self-organization maps in a case-based reasoning system

A. Fornells, E. Golobardes, J. M. Martorell, J. M. Garrell, E. Bernadó, N. Macià

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

4 Cites (Scopus)

Resum

Case-Based Reasoning (CBR) systems solve new problems using others which have been previously resolved. The knowledge is composed of a set of cases stored in a case memory, where each one describes a situation in terms of a set of features. Therefore, the size and organization of the case memory influences in the computational time needed to solve new situations. We organize the memory using Self-Organization Maps, which group cases with similar properties into patterns. Thus, CBR is able to do a selective retrieval using only the cases from the most suitable pattern. However, the data complexity may hinder the identification of patterns and it may degrade the accuracy rate. This work analyses the successful application of this approach by doing a previous data complexity characterization. Relationships between the performance and some measures of class separability and the discriminative power of attributes are also found.

Idioma originalAnglès
Títol de la publicacióPattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings
EditorSpringer Verlag
Pàgines532-539
Nombre de pàgines8
EdicióPART 2
ISBN (imprès)9783540728481
DOIs
Estat de la publicacióPublicada - 2007
Esdeveniment3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007 - Girona, Spain
Durada: 6 de juny 20078 de juny 2007

Sèrie de publicacions

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NombrePART 2
Volum4478 LNCS
ISSN (imprès)0302-9743
ISSN (electrònic)1611-3349

Conferència

Conferència3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007
País/TerritoriSpain
CiutatGirona
Període6/06/078/06/07

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