An integrated updating Algorithm for mining maximal frequent patterns

The problem of mining maximal frequent patterns plays an essential role in mining association rules. In order to discover more useful maximal frequent patterns, users may adjust the minimum support while database changes. Therefore, we present a novel algorithm IUMFPA that makes use of improved FP-Tree structure and bit object for data expression. It can also utilize the former FP-Tree and the mined results sufficiently. The experimental results indicate that IUMFPA performs efficiently.