An improvement algorithm for FP-growth
Jun Chen · Journal of Xi'an University of Science and Technology · 2009
In the association rule's mining,FP-growth algorithm is one of the high effective algorithm,although it does not produce the candidate sets,still needs traversal result sets L many times.To solve this problem,an improved algorithm HFP-growth(Hash FP-growth)was proposed.HFP-growth stored data in the result sets L into the hash table by its item name which corresponded to its support counts.When looking for some support counts a corresponding result can be returned only to input a item name into the hash table,which saves much time in traversing result sets L.Experiment result shows that HFP-growth algorithm outperform FP-growth and can be applied in Online Recruitment System.