Bounded Rationality for Data Reasoning Based on Formal Concept Analysis

Author

Aranda-Corral, Gonzalo A. ; Borrego-Díaz, Joaquín ; Galan-Paez, Juan

Author_Institution

Dept. of Inf. Technol., Univ. de Huelva, Palos de La Frontera, Spain

fYear

2011

fDate

Aug. 29 2011-Sept. 2 2011

Firstpage

350

Lastpage

354

Abstract

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.

Keywords

data mining; formal concept analysis; inference mechanisms; sport; association rules; bounded rationality; contextual selection; data reasoning; formal concept analysis; knowledge discovery; knowledge extraction; sport result forecasting; Association rules; Biological system modeling; Cognition; Context; Context modeling; Forecasting; Production systems; Bounded Rationality; Confidence Reasoning; Formal Concept Analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Database and Expert Systems Applications (DEXA), 2011 22nd International Workshop on

Conference_Location

Toulouse

ISSN

1529-4188

Print_ISBN

978-1-4577-0982-1

Type

conf

DOI

10.1109/DEXA.2011.18

Filename

6059842