Abstract: Association rule mining is an important method to analyze the associated faults of the airborne network and improve the efficiency of faults diagnosis process.This paper analyzed the limitations of the classical Apriori algorithm,and proposed an efficient association rule mining algorithm,which is based on the knowledge of the airborne network,matrix operation and frequent item sets.Due to the association characteristics of the airborne network faults based on the application paths,this paper proposed a mining strategy of block mining,so as to realize the noise isolation in mining process.With the conception of frequency matrix and feature vector,5 kinds of scanning strategies were proposed,thereby reducing the number of cycles and the comparison operation.Comparing with the classical Apriori algorithm,the new algorithm can effectively improve the search efficiency of frequent itemsets.

Key words: Association rules,Association faults,Application paths,Block mining,Frequency matrix