Ponencia
Bounded Rationality for Data Reasoning based on Formal Concept Analysis
Autor/es | Aranda Corral, Gonzalo A.
Borrego Díaz, Joaquín Galán Páez, Juan |
Departamento | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Fecha de publicación | 2011 |
Fecha de depósito | 2018-05-18 |
Publicado en |
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ISBN/ISSN | 978-1-4577-0982-1 1529-4188 |
Resumen | Formal Concept Analysis (FCA) is a theory whose goal is to discover and extract Knowledge from qualitative data. It also provides tools for sound reasoning (implication basis and association rules). The aim of this paper ... Formal Concept Analysis (FCA) is a theory whose goal is to discover and extract Knowledge from qualitative data. It also provides tools for sound reasoning (implication basis and association rules). The aim of this paper is to apply FCA to a new model for bounded rationality based on the implicational reasoning over contextual knowledge bases which are obtained from contextual selections. A contextual selection is a selection of events and attributes about them which induces partial contexts from a global formal context. In order to avoid inconsistencies, association rules are selected as reasoning engine. The model is applied to forecast sport results. |
Agencias financiadoras | Ministerio de Ciencia e Innovación (MICIN). España Junta de Andalucía |
Identificador del proyecto | TIN2009-09492
TIC-6064 |
Cita | Aranda Corral, G.A., Borrego Díaz, J. y Galán Páez, J. (2011). Bounded Rationality for Data Reasoning based on Formal Concept Analysis. En DEXA 2011: 22nd International Workshop on Database and Expert Systems Applications (350-354), Toulouse, France: IEEE. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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Bounded Rationality.pdf | 358.8Kb | [PDF] | Ver/ | |