Mining algorithm for weighted FP-tree frequent item sets based on two-dimensional table

FP-growth algorithm is a classic algorithm of mining frequent item sets, but there exist certain disadvantages for mining the weighted frequent item sets. Based on the weighted downward closure property of the weighted model, this paper proposed that the weighted support was recorded in the two-dimensional table. This method has saved the process to search for the first conditional pattern base by traversing the weighted FP-tree, improved the efficiency of the weighted frequent item sets generated.