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

Fang Huang | Zendy; Ningning Zheng | Zendy

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

Author(s) -

Fang Huang,

Ningning Zheng

Publication year - 2019

Publication title -

traitement du signal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.279

H-Index - 11

eISSN - 1958-5608

pISSN - 0765-0019

DOI - 10.18280/ts.360103

Subject(s) - radar , computer science , data stream , data mining , algorithm , artificial intelligence , geology , telecommunications

Received: 29 December 2018 Accepted: 22 January 2019 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.

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