1. 陆军军医大学(第三军医大学 机构 ) 生物医学工程系 医学图像学教研室,重庆,400038
2. 国防科技大学 计算机学院,湖南,长沙,410073
3. 武警警官学院 信息通信系,四川,成都,610213
纸质出版:2018
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李鹏岳, 何杰, 谭志国. 基于类Apriori原则的区域周期模式挖掘算法[J]. 微电子学与计算机, 2018, 35(9): 85-89.
LI Peng-yue, HE Jie, TAN Zhi-guo. A Regional Periodic Pattern Mining Algorithm Based on Apriori-like Principle[J]. 2018, 35(9): 85-89.
时间序列在各领域广泛存在
针对目前已有的周期模式难以描述仅在时间序列部分区域存在的周期行为的现状
提出了区域周期模式的概念.在对此区域周期模式进行详细形式化描述的基础上
进一步提出了一种基于类Apriori原则的区域周期模式挖掘算法.该算法能在保证挖掘结果完整性的同时
较大程度地提高挖掘效率.通过在网络安全公开数据集上的实验表明
该算法能快速精确地挖掘出时间序列中所有的区域周期模式.
Time series exists widely in various fields. In view of the fact that the existing periodic models are difficult to describe periodic behaviors only activate in partial regions of time series
a novel concept called regional periodic pattern is proposed. After formalizing this regional periodic pattern
a regional periodic pattern mining algorithm based on apriori-like principle is further proposed
which can greatly improve the efficiency of mining under the premise of ensuring the integrity of the mining results. Experiments on a public dataset of network security show that the proposed algorithm can quickly and accurately mine all regional periodic patterns in time series.
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