Selecting Attributes for Sport Forecasting using Formal Concept Analysis
  In order to address complex systems, apply pattern recongnition on their
evolution could play an key role to understand their dynamics. Global patterns
are required to detect emergent concepts and trends, some of them with
qualitative nature. Formal Concept Analysis (FCA) is a theory whose goal is to
discover and to extract Knowledge from qualitative data. It provides tools for
reasoning with implication basis (and association rules). Implications and
association rules are usefull to reasoning on previously selected attributes,
providing a formal foundation for logical reasoning. In this paper we analyse
how to apply FCA reasoning to increase confidence in sports betting, by means
of detecting temporal regularities from data. It is applied to build a
Knowledge-Based system for confidence reasoning.
