基于抽样技术的序列模式的维护

The Maintenance of Sequential Patterns Based on Sampling Techniques

维护已发现的序列模式的方法主要有两种：一种是简单地利用已有的挖掘序列模式算法对更新后的整个数据库进行操作，这种方法涉及的数据库中的数据不仅有改变的部分而且有未改变的部分，而未改变的数据数量很大，当更新频率高时，代价是非常大的；另一种方法是根据库中记录数目改变的多少来决定何时对整个数据库进行操作，但是记录数目变化大并不能代表序列模式变化亦大，因此利用样品抽样的方法来评估序列模式改变的程度，并根据改变的程度决定何时对整个数据库进行操作来更新序列模式，从而较好地解决序列模式维护的问题，能高效地、准确地发现序列模式。

The methods to solve the problem of maintaining discovered sequential patterns have mainly two kinds. One is simply applying algorithms of mining sequential patterns to the updated database, but it scans not only changed data but also unchanged data in the original database which is very large. If the database is updated frequently, it takes much time. Another is according to the number of records changed in the database to decide when to operate the whole database, but the number of sequential patterns changed is not in proportion to the number of records changed. So we use sampling techniques to estimate the degree of sequential patterns changed to determine whether we should update mined sequential patterns by operating the whole database or not. This can solve better the problem and find sequential patterns efficiently and exactly.