Arithmetic Design Of Multidimensional Association Rule

Data Mining, also named as KDD (Knowledge Discovery in Database), is an advanced process in which we can pick up many trustful, novel, useful and readable patterns from very large amounts of data, and Association Rule is one of the 6 ways of data modes. From the Market Basket Analysis to processing analysis of flood data in Telecommunications, Banking, Association Rule has been already widely put into practical application in the commercial field, in which searching Multidimensional Association Rule from flood data are potential endless.Tradition Apriori Arithmetic is the common arithmetic of searching Boolean Association Rule based on the one-dimensional database, of which the shortcomings is also obvious by its lower efficiency and the use of a limited range, while it also can't be applied in searching Multidimensional Association Rule. Based on the original Apriori Arithmetic, the article designs the Arithmometer Arithmetic itself, which through the independent count to the target object database, effectively found a way to searching Multidimensional Association Rule, which provided additional technical support for Association Rule Mining of multidimensional database.In addition to breaking the limitation of inapplicability in searching Multidimensional Association Rule by original Apriori Arithmetic, the biggest advantage of the Arithmometer Arithmetic lies in that through the entire process of searching for Multidimensional Association Rule, it needs scan the target database only once, which greatly reduce the burden on the system, especially in the Association Rule Mining to the flood of data or remote database, improving the operation efficiency of the entire arithmetic.Through computer-translation procedures, using the real client data of telecommunications enterprise, the article succeeded in searching and saving the Multidimensional Association Rule, which achieved the practical application of the...