Association Rules is an important field in Data Mining, which is
used to discover useful knowledge from a massive databases.
Association Rules have been used to extract the information from
the database transactions, and Apriori Algorithm is a pra
ctical
application for Association Rules and it is used to find frequent
itemsets from database transactions. In this paper, we present a
new improving on Apriori Algorithm by reduction generating of
candidate itemsets and this leads to improving efficiency Apriori
Algorithm.
