21-05-2014, 12:48 PM
2. Fast Algorithms for Mining Association Rules in Large Databases
ABSTRACT
In this paper they consider the problem of association rules between items in large database of sales transaction. They present two new algorithms Apriori and AprioriTid for discovering all significant association rule between items in large database of transactions. They compared these algorithms with the previously known algorithms for frequent pattern mining. The conclusion of this paper is that the performance of new algorithms is better than the previously known algorithms. They showed how the best features of the two proposed algorithms can be combined into hybrid algorithm, called AprioriHybrid. Experimental results showed that AprioriHybrid scales linearly with number of transactions. In addition the execution time decreases a little as the number of items in the database increases. These experiments demonstrates the feasibility of AprioriHybrid in real applications involving very large databases.