One Scan is Enough: Optimising Association Rules Mining

Data mining is as a new area of research has taken its place as one of the most important techniques in the decision making process. Mining association rules is one of simple yet powerful technique in the data mining process The problem of mining association rules is composed of finding the large itemsets and to generate the association rules from these itemsets. Usually the dataset must be scanned many times in order to find the large itemsets. Many algorithms have been developed to increase the performance of mining association rules through reducing the number of scans over the dataset. This work aims to enhance and optimise the process even further by developing techniques to reduce the number of database scans to just only one.