Using entropy-based local weighting to improve similarity assessment

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Título:	Using entropy-based local weighting to improve similarity assessment
Autor/a:	Núñez, Héctor; Sànchez-Marrè, Miquel; Cortés García, Claudio Ulises; Comas, Joaquim; Rodriguez-Roda, Ignasi; Poch, Manel
Otros autores:	Universitat Politècnica de Catalunya. Departament de Ciències de la Computació; Universitat Politècnica de Catalunya. KEMLG - Grup d'Enginyeria del Coneixement i Aprenentatge Automàtic
Abstract:	This paper enhances and analyses the power of local weighted similarity measures. The paper proposes a new entropy-based local weighting algorithm to be used in similarity assessment to improve the performance of the CBR retrieval task. It has been carried out a comparative analysis of the performance of unweighted similarity measures, global weighted similarity measures, and local weighting similarity measures. The testing has been done using several similarity measures, and some data sets from the UCI Machine Learning Database Repository and other environmental databases.
Materia(s):	-Àrees temàtiques de la UPC::Informàtica -Entropy -Similarity -CBR -UCI machine learning database repository -Local weighted similarity measures
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Tipo de documento:	Artículo - Versión publicada Informe
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Núñez, Héctor; Sànchez-Marrè, Miquel; Cortés García, Claudio Ulises; Comas, Joaquim; Rodríguez Roda, Ignasi; Poch, Manel

Belanche Muñoz, Luis Antonio; Valdés Ramos, Julio José; Comas, Joaquim; Rodriguez-Roda, Ignasi; Poch, Manel

Poch Espallargas, Manel; Comas Matas, Joaquim; Cortés García, Claudio Ulises; Sànchez-Marrè, Miquel; Rodriguez-Roda, Ignasi

Serra, Pau; Sànchez-Marrè, Miquel; Lafuente Sancho, Francisco Javier; Cortés García, Claudio Ulises; Poch, Manel

Aulinas, Montse; Tolchinsky Landsmann, Francisco; Turon, Clàudia; Poch, Manel; Cortés García, Claudio Ulises

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