A Novel Frequent Pattern Mining Algorithm for Real-time Radar Data Stream

被引：2
|
作者：
Huang, Fang [1 ]
Zheng, Ningning [1 ]
机构：
[1] Shandong Agr & Engn Univ, Informat Sci & Engn Coll, Jinan 250100, Shandong, Peoples R China
来源：
TRAITEMENT DU SIGNAL | 2019年 / 36卷 / 01期
关键词：
frequent pattern; data mining; radar data; data stream; index pattern tree (IPT); SLIDING WINDOW; ITEMSETS;
D O I：
10.18280/ts.360103
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper attempts to improve the radar data quality and discover intrusion behaviors by mining frequent patterns of real-time data. For this purpose, the author improved the frequent pattern mining algorithm for static datasets, and proposed a maximum frequent pattern mining algorithm based on bitmap mapping. Next, a new frequent pattern mining algorithm was designed specifically for data stream with the storage structure of index pattern tree (IPT). The new algorithm was applied to process the real-time radar data stream. The application results demonstrate efficiency of our algorithm in time and space.
引用
收藏
页码：23 / 30
页数：8
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