Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/52073
Title: Model driven engineering for data miners simulation
Authors: Évora Gómez, José 
Hernández Cabrera, José Juan 
Hernandez, Mario 
UNESCO Clasification: 1203 Ciencia de los ordenadores
Keywords: Complex systems
Data miners
Data mining
Decision making
Decision support systems, et al
Issue Date: 2013
Project: Framework Para la Simulación de la Gestión de Mercado y Técnica de Redes Eléctricas Insulares Basado en Agentes Inteligentes. Caso de la Red Eléctrica de Gran Canaria. 
Abstract: Decision making processes in some contexts, such as construction of infrastructures, require the design of prospective experiments. These experiments are designed to test hypothesis raised in the design phase. Following an adaptive methodology, these experiments will feed new iterations. In many cases, the development of these experiments is so costly that they must be performed using simulators. In this paper, an approach for developing data mining simulators based on Model Driven Engineering is presented. These miners can be fed from data stores (i.e. multidimensional data stores) and may generate new data stores with the results they provide. This approach is intended to reduce the uncertainty at decision making as well as to speed up the iterative process.
URI: http://hdl.handle.net/10553/52073
ISBN: 978-1-4799-3142-2
ISSN: 2375-9232
DOI: 10.1109/ICDMW.2013.141
Source: Proceedings - IEEE 13th International Conference on Data Mining Workshops, ICDMW 2013 (6753944), p. 370-376
Appears in Collections:Actas de congresos
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