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。
Experimental results showed that computation of condensed frequent sequential pattern base is promising.
实验结果显示计算频繁序列模式精简基是很有前途的。
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。
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。
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。
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