An Incremental and Hash-based Algorithm for Mining Frequent Episodes

Episodes rules can describe and predict the behavior of the event sequences. The property of incremental frequent episodes mining is studied and the related lemmas and corollaries are presented, then a general incremental algorithm named IHE for mining frequent episodes is proposed. Moreover, it proposes and utilizes the window-hash-based technique to prune candidate episodes. The performance of the algorithm IHE was evaluated and compared with the algorithm WINEPI. It is shown by our experimental results that the algorithm IHE has better performance