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Flexible knowledge representation and new similarity measure: Application on case based reasoning for waste treatment

Chazara, Philippe and Negny, Stéphane and Montastruc, Ludovic Flexible knowledge representation and new similarity measure: Application on case based reasoning for waste treatment. (2016) Expert Systems with Applications, 58. 143-154. ISSN 0957-4174

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Official URL: https://doi.org/10.1016/j.eswa.2016.03.014

Abstract

In Case Based Reasoning the representation of a case and the similarity measures are two difficult steps in the conception of a system. Often, these steps are developed to resolve one kind of problem. However, in some of them such as recovery treatment processes generation, it is necessary for the system to be able to modify and adapt the representation of a case and the similarity measures with respect of the context and also the kind of solutions proposed. In this paper, authors introduce a new method to represent cases with a flexibility based on a structure in a connectionist model. This flexibility is needed due to the complexity of cases, the number of possible options and to ensure the durability of the system. In a second main contribution, authors introduce a method for the selection of source cases using abstraction, conceptualisation and inference mechanisms. Finally, authors test their system in a CBR developed on SWI-Prolog with different problems. The CBR is applied to find new recovery processes and try to estimate the new upgraded product generated.

Item Type:Article
HAL Id:hal-01900381
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
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Deposited By: Loetitia MOYA
Deposited On:19 Oct 2018 09:44

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