Efficient Mining of Association Rules Based on Formal Concept Analysis
L. Lakhal, und G. Stumme. Volume 3626 von LNAI, Seite 180-195. Springer, Heidelberg, (2005)
Zusammenfassung
Association rules are a popular knowledge discovery technique for
warehouse basket analysis. They indicate which items of the
warehouse are frequently bought together. The problem of association
rule mining has first been stated in 1993. Five years later, several
research groups discovered that this problem has a strong connection
to Formal Concept Analysis (FCA). In this survey, we will first
introduce some basic ideas of this connection along a specific
algorithm, \titanic, and show how FCA helps in reducing the number
of resulting rules without loss of information, before giving a
general overview over the history and state of the art of applying
FCA for association rule mining.
