One database pass algorithms of mining top-k frequent closed itemsets

The FP-growth algorithm is a powerful algorithm to mine frequent patterns and it is non-candidate generation algorithm using a special structure FP-tree. Many algorithms proposed recently are based on FP-tree. These algorithms include all frequent itemsets mining, closed frequent itemsets mining and top-k closed frequent itemsets mining. However, it still requires two database scans, Although it is not a problem for static database, it is not efficient for frequent pattern mining, interactive and incremental mining. In order to enhance the efficiency of FP-tree based algorithms, propose a novel algorithm called QFPC which can create FP-tree with one database pass. Also propose a novel algorithm PFPTC to create FP-tree parallelly.