Objective Present a new features selection algorithm. Methods based on rule induction and field knowledge. Results This algorithm can be applied in catching dataflow when detecting network intrusions, only the sub ...Objective Present a new features selection algorithm. Methods based on rule induction and field knowledge. Results This algorithm can be applied in catching dataflow when detecting network intrusions, only the sub dataset including discriminating features is catched. Then the time spend in following behavior patterns mining is reduced and the patterns mined are more precise. Conclusion The experiment results show that the feature subset catched by this algorithm is more informative and the dataset’s quantity is reduced significantly.展开更多
严格遵循数据挖掘的步骤,采用时间序列挖掘算法,结合微软的BI数据挖掘工具（SQL Server Business Intelligence Development Studio）对从数据堂[9]上采集的数据集进行建模,从而挖掘出在特定时间段内用户的上网行为模式和潜在的上网规律...严格遵循数据挖掘的步骤,采用时间序列挖掘算法,结合微软的BI数据挖掘工具（SQL Server Business Intelligence Development Studio）对从数据堂[9]上采集的数据集进行建模,从而挖掘出在特定时间段内用户的上网行为模式和潜在的上网规律,对校园网络的科学管理提出了合理的建议。展开更多
文摘Objective Present a new features selection algorithm. Methods based on rule induction and field knowledge. Results This algorithm can be applied in catching dataflow when detecting network intrusions, only the sub dataset including discriminating features is catched. Then the time spend in following behavior patterns mining is reduced and the patterns mined are more precise. Conclusion The experiment results show that the feature subset catched by this algorithm is more informative and the dataset’s quantity is reduced significantly.
文摘严格遵循数据挖掘的步骤,采用时间序列挖掘算法,结合微软的BI数据挖掘工具（SQL Server Business Intelligence Development Studio）对从数据堂[9]上采集的数据集进行建模,从而挖掘出在特定时间段内用户的上网行为模式和潜在的上网规律,对校园网络的科学管理提出了合理的建议。
