The sequence analysis is a two-stage process for sequential pattern mining 1.
顺序分析是一个两阶段的顺序模式挖掘流程1。
This paper presents and implements a macro-network traffic anomaly detection strategy based on sequential frequent pattern mining.
基于序贯频繁模式挖掘，提出并实现了一种宏观网络流量异常检测的方法。
Sequential pattern mining, which discovers frequent subsequences as interesting patterns in a sequence database.
序列模式挖掘就是发现序列数据库中的频繁子序列作为用户感兴趣的模式。
How to generate candidate frequent sequential pattern and calculate its support is a key problem in mining frequent sequential patterns.
如何确定候选频繁序列模式以及如何计算它们的支持数是序列模式挖掘中的两个关键问题。
The sequential pattern is a very useful knowledge one in time related databases, and it is very important to find out high efficient algorithm of mining it.
序贯模式是时间相关数据库中存在的一种十分有用的知识模式，其发掘方法的研究有着十分重要的意义。
The 3-D pattern on sequential stratigraphy proposed by Vail et. al (1988, 1989) can be considered as a basis on which their new idea of sequential stratigraphy is established.
维尔等人（1988，1989）提出的层序地层立体模式，可以说是他们的层序地层学新概念立论的基础，也是他们赖于进行地层和岩相解释的依据。
The 3-D pattern on sequential stratigraphy proposed by Vail et. al (1988, 1989) can be considered as a basis on which their new idea of sequential stratigraphy is established.
维尔等人（1988，1989）提出的层序地层立体模式，可以说是他们的层序地层学新概念立论的基础，也是他们赖于进行地层和岩相解释的依据。
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