在這篇文章中，我們提出了一種應用抽樣的技術于序列挖掘的算法。這個方法能在原
始數據庫和更新后的數據庫之間評價序列模式的變化。評價了序列模式的變化我們能決定何時使用精確的挖掘算法或增量算法：如果變化達到一定程度，就使用精確的方法以挖掘新的序列模式；如果變化比較小，則在一定的可信度情況下，就使用原來的模式，且誤差能控制在一定的范圍內。
關鍵字：抽樣，數據挖掘，序列，置信區間
Abstract : In this paper, we use sample method into sequence pattern mining and devise a
algorithm. This method can estimate the changes of patterns in a database when it is updated.
When we estimate the changes of patterns, we can make a decision about the time to use an exact mining algorithm or an incremental algorithm: if the changes reach a certain degree, exact method will be used in order to mine new sequence patterns; if the change is little, we can use the original patterns under a certain reliability, and the error can be controlled in certain bound.
Key words: sample, data mining, sequence, confidence interval.