  Association Rule mining is one of the most important fields in data mining
and knowledge discovery. This paper proposes an algorithm that combines the
simple association rules derived from basic Apriori Algorithm with the multiple
minimum support using maximum constraints. The algorithm is implemented, and is
compared to its predecessor algorithms using a novel proposed comparison
algorithm. Results of applying the proposed algorithm show faster performance
than other algorithms without scarifying the accuracy.
