Using entropy-based local weighting to improve similarity assessment

Home | About RECERCAT | Contact

Català | Castellano

All of RECERCAT

By Communities &
Collections By Defense Date By Authors By Titles By Subject

This Collection

By Defense Date By Authors By Titles By Subject

Statistics

View Statistics All RECERCAT

My RECERCAT

Other repositories directory

RECERCAT Home > Universitat Politècnica de Catalunya > Documents de recerca > View document

To access the full text documents, please follow this link: http://hdl.handle.net/2117/97483

dc.contributor	Universitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.contributor	Universitat Politècnica de Catalunya. KEMLG - Grup d'Enginyeria del Coneixement i Aprenentatge Automàtic
dc.contributor.author	Núñez, Héctor
dc.contributor.author	Sànchez-Marrè, Miquel
dc.contributor.author	Cortés García, Claudio Ulises
dc.contributor.author	Comas, Joaquim
dc.contributor.author	Rodriguez-Roda, Ignasi
dc.contributor.author	Poch, Manel
dc.date	2002-06
dc.identifier.citation	Núñez, H., Sanchez, M., Cortes, C., Comas, J., Rodriguez-Roda, I., Poch, M. "Using entropy-based local weighting to improve similarity assessment". 2002.
dc.identifier.uri	http://hdl.handle.net/2117/97483
dc.language.iso	eng
dc.relation	LSI-02-48-R
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Informàtica
dc.subject	Entropy
dc.subject	Similarity
dc.subject	CBR
dc.subject	UCI machine learning database repository
dc.subject	Local weighted similarity measures
dc.title	Using entropy-based local weighting to improve similarity assessment
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/report
dc.description.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.

Show simple item record

All of RECERCAT

This Collection

Statistics

My RECERCAT

Related documents

Other documents of the same author