Apriori Algorithm is an influential algorithm for mining frequent itemsets for boolean association rules. It uses a “bottom up” approach, where frequent subsets are extended one item at a time, a step known as candidate generation, and groups of candidates are tested against the data. Apriori Algorithm is designed to operate on database containing transactions. It also proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database.