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Optimizing network traffic by generating association rules using Hybrid Apriori-Genetic algorithm

机译:使用混合APRIORI-Genetic算法生成关联规则优化网络流量

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摘要

Association rule mining is a technique of generating frequent item sets so that the analysis on the basis of these sets can be used for different application areas such as analysis of network traffic. Although the frequent sets generated using apriori algorithm provides less computational time and provides less frequent sets, but the technique that we are implemented here provides less computational time as compared as well generated less sets and provides less rules for the network traffics. These frequent sets are used for the analysis of traffic in the network so that the analysis of different spams or any unwanted issues can be detected easily.
机译:关联规则挖掘是一种生成频繁项目集的技术,以便基于这些集合的分析可用于不同的应用领域,例如网络流量分析。尽管使用APRIORI算法生成的频繁设置提供了较少的计算时间并提供较少的频率集,但是在此处实现的技术提供了较少的计算时间,而相比,相比,生成的设置较少并提供了更少的网络流量规则。这些频繁的集合用于分析网络中的流量,以便容易地检测对不同垃圾邮件或任何不需要的问题的分析。

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