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Introducing the Discriminative Paraconsistent Machine (DPM)

Authors :
Guido, Rodrigo Capobianco
Barbon, Sylvio
Solgon, Regiane Denise
Silva Paulo, Kátia Cristina
Rodrigues, Luciene Cavalcanti
da Silva, Ivan Nunes
Lemos Escola, João Paulo
Source :
Information Sciences. Feb2013, Vol. 221, p389-402. 14p.
Publication Year :
2013

Abstract

Abstract: This paper introduces a new tool for pattern recognition. Called the Discriminative Paraconsistent Machine (DPM), it is based on a supervised discriminative model training that incorporates paraconsistency criteria and allows an intelligent treatment of contradictions and uncertainties. DPMs can be applied to solve problems in many fields of science, using the tests and discussions presented here, which demonstrate their efficacy and usefulness. Major difficulties and challenges that were overcome consisted basically in establishing the proper model with which to represent the concept of paraconsistency. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
00200255
Volume :
221
Database :
Academic Search Index
Journal :
Information Sciences
Publication Type :
Periodical
Accession number :
83324156
Full Text :
https://doi.org/10.1016/j.ins.2012.09.028