Mining Algorithm for Weighted Frequent Pattern Based on Fp Tree
Wen Chen · Jisuanji gongcheng · 2012
This paper presents a new algorithm for mining weighted frequent item sets without generating candidate.A weight set of attributes is normalized to avoid weighted approval rate greater than 1.The new algorithm is testified to satisfy weighted downward closure property.An effectively mining pruning strategy based on weighed Fp-tree is structured.Example analysis and experimental results show that the algorithm can reduce the weighted frequent item sets formation process of computation,and improve weighted frequent item sets generation efficiency.