Mining Algorithm for Weighted FP-Growth Frequent Item Sets based on Ordered FP-Tree

Abstract

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 a method to reduce the use of storage space by constructing a weight ordered FP-tree, so as to improve the generation efficiency of weighted frequent item sets.