基于改进谱聚类的正则表达式分组算法

Regular Expression Grouping Algorithm Based on Improved Spectral Clustering

提出一种面向全局的正则表达式分组算法,即通过拉普拉斯矩阵将规则集合映射到具有明显聚类现象的空间中,将分组问题转化为传统的空间聚类问题,然后运用初始点优化的KMeans聚类方法实现快速分组。实验结果表明,在相同分组数的情况下,该算法的内存占用较GABG算法减少了10%左右,分组时间上缩短了2倍~3倍,实现了分组时间和分组效果的有效平衡。

With the abundance of traffic and the development of detense technology, the existing reg- ular expression grouping algorithm is more and more difficuh to meet the growing storage demand. This paper puts torward a regular expression grouping algorithm with global orientation. Firstly, the rules set is mapped into the teature vector space with obvious clustering phenomenon by laplacian matrix. Then the improved K-Means clustering method is designed to realize fast grouping. Experi- mental results show that the algorithm can achieve the effective balance of grouping time and group- ing ettect. Compared with the current GABG algorithm, the algorithm can reduce 10% memory us- age for the same number of groups, and reduce the grouping time by two to three times.