Abstract: Popular assessment of the faults of Apriori association rule mining algorithm required to scan database regularly and create a standard of huge aspirant. The binary sequence remained to use and prompt facts granule, using grain-bit binary abstraction frequent item sets and determining association rules. This allows the possibility to extract, analyse and organize information and knowledge through relationships between granules and between granulations Through research, the classical Apriori algorithm and the system that established on granular computing association rules extraction keep on associated to the experimental results are evaluated. The results illustrate that the algorithm for mining association rules based on granular computing for mining association rules is realistic and in effect.

Keywords: Association Rule Mining, Granular Computing, Apriori algorithm.