A fast distributed algorithm for association rule mining based on binary coding mapping relation
Geng Chen, Weiwei Ni, Yuquan Zhu, Sun Zhi-hui · Wuhan University Journal of Natural Sciences · 2006
Association rule mining is an important issue in data mining. The paper proposed an binary system based method to generate candidate frequent itemsets and corresponding supporting counts efficiently, which needs only some operations such as “and”, “or” and “xor”. Applying this idea in the existed distributed association rule mining algorithm FDM, the improved algorithm BFDM is proposed. The theoretical analysis and experiment testify that BFDM is effective and efficient.