Efficient algorithms of mining top-k frequent closed itemsets

Top-k frequent closed itemsets mining has been studied extensively in data mining community. But the I/O cost of database scanning is still a bottle-neck problem in data mining. TFP-growth is a powerful algorithm to mine Top-k frequent closed itemsets and it is non-candidate generation algorithm using a special structure FP-tree. Many algorithms proposed recently are based on FP-tree. However, creating, FP-tree from database must scan database two times. In order to enhance the efficiency of TFP- growth algorithms, propose a novel algorithm called QFPC which can create FP-tree with one database scanning. With QFPC, we can mine top-k frequent closed itemsets Efficiently