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.
In order to reduce the computational and spatial complexity in rerunning algorithm of sequential patterns query, this paper proposes sequential patterns based and projection database based algorithm for fast interactive sequential patterns mining algorithm (FISP), in which the number of frequent items of the projection databases constructed by the correct mining which based on the previously mined sequences has been reduced. Furthermore, the algorithm’s iterative running times are reduced greatly by using global-threshold. The results of experiments testify that FISP outperforms PrefixSpan in interactive
LU Jie-PingLIU Yue-boNI wei-weiLIU Tong-mingSUN Zhi-hui
