在這篇文章中，我們提出了一種應(yīng)用抽樣的技術(shù)于序列挖掘的算法。這個(gè)方法能在原
始數(shù)據(jù)庫和更新后的數(shù)據(jù)庫之間評價(jià)序列模式的變化。評價(jià)了序列模式的變化我們能決定何時(shí)使用精確的挖掘算法或增量算法：如果變化達(dá)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(nèi)。
關(guān)鍵字：抽樣，數(shù)據(jù)挖掘，序列，置信區(qū)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.