English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/60486
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:


A logical approach to case-based reasoning using fuzzy similarity relations

AuthorsPlaza, Enric ; Esteva, Francesc ; García-Calvés, Pere ; Godo, Lluis ; López de Mántaras, Ramón
Issue Date1998
CitationInformation Sciences 106: 105- 122 (1998)
AbstractThis article approaches the formalization of inference in Case-based Reasoning (CBR) systems. CBR systems infer solutions of new problems on the basis of a precedent case that is, to some extent, similar to the current problem. Using the logics developed for similarity-based inference we characterize CBR systems defining what we call the Precedent-based Plausible Reasoning (PPR) model. This model is based on the graded consequence relations named approximation entailment and proximity entailment. A modal interpretation is provided for the precedent-based inference where the plausibility is given by the graded possibility operator ◇α-The PPR model shows that both knowledge-intensive CBR systems and the nearest neighbor algorithms share a common core formalism and that their difference is on whether or not (respectively) they use a general theory in addition to the precedent cases. © 1998 Elsevier Science Inc. All rights reserved.
Appears in Collections:(IIIA) Artículos
Files in This Item:
File Description SizeFormat 
accesoRestringido.pdf15,38 kBAdobe PDFThumbnail
Show full item record
Review this work

Related articles:

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.