Bounded Rationality for Data Reasoning Based on Formal Concept Analysis

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.