Application Of Association Rules Based On Fuzzy Concept Analysis

This paper applies the Association Rule to the attribute reduction in fuzzy concept lattice, and proposes the concept of Association of attribute reduction, then successfully applies it to confirm decisive diagnostic symptoms, which provides a new basis for Artificial Intelligent Diagnosis. Moreover, Association Rule is used to simplify the data. Finally it is proved that only two symptoms are most effective ones to diagnosis the rheum, which provides a new basis for artificial intelligence diagnostics. Moreover, for incomplete concept lattice, this paper finds a new approach to repair the data, that is Association Rule, which achieved good results. The main results are summarized as follows:Part One:We introduce Formal Concept Analysis and Fuzzy Theory, then combine them and give examples to explain.Part Two:This part gives the definition of Association Rule and its applications, then gives the theory of Association of attribute reduction and Association rules for data reparation.Part Three:We set the flu as an example, firstly fuzzy the data, and then use the concept lattice to simplify the data, finally Association Rule is used to have a deep data mining and we obtain the simplified data. Moreover, for the incomplete concept lattices, we also use Association Rule to repair the data and achieved good results.