Single-pass based efficient erasable pattern mining using list data structure on dynamic incremental databases

摘要: Abstract Many different approaches of data mining have been proposed to satisfy various demands users. Erasable pattern is one the interesting areas in frequent mining, which was diagnose and solve financial problems caused industrial fields. Since its original concept emerged, relevant devised. Analyzing incremental becomes more important because are continually accumulated application fields including areas. For this reason, an method for erasable has also suggested order reflect such a trend. become gradually larger complicated with passage time, it process as quickly efficiently possible. However, previous limitations respect. Motivated by challenge, we propose new algorithm structures techniques efficient processing. We demonstrate that outperforms state-of-the-art through extensive, empirical performance tests.