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Improved Prefixspan algorithm-based radar data frequent pattern mining method

A technology of radar data and frequent patterns, applied in visual data mining, electrical digital data processing, structured data retrieval, etc., to achieve the effect of saving memory and reducing the number of times to scan the original database

Inactive Publication Date: 2018-05-25
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0005] The present invention provides a radar data frequent pattern mining method based on the improved Prefixspan algorithm for the deficiencies of the prior art, which solves the difficulty of mining frequent patterns in the existing algorithm, such as the need to scan the data set multiple times and construct a large number of projections Database, multi-pass scan projection database for statistical calculation of the support degree of the sequence

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  • Improved Prefixspan algorithm-based radar data frequent pattern mining method
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  • Improved Prefixspan algorithm-based radar data frequent pattern mining method

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[0038] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0039] refer to figure 1 , a radar data frequent pattern mining method based on the improved Prefixspan algorithm. Before mining frequent patterns, it is first necessary to divide the sequence to be mined into signal sources, data preprocessing, etc., and then divide the preprocessed data into blocks. Then read a block of data for bitmap mapping, and finally perform frequent pattern mining on the block data through an improved mining algorithm.

[0040] In the process of using the improved algorithm for pattern mining, data preprocessing is a very important work. Because the actual radar signal data contains a lot of noise, it cannot be directly used for pattern mining. It is necessary to denoise the original data to make it suitable for pattern mining. After data preprocessing, due to the infinity of the data, it is impossible to read all t...

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Abstract

The invention discloses an improved Prefixspan algorithm-based radar data frequent pattern mining method, belongs to the field of data mining, and solves the problems of multi-time scanning of an original database, consumption of large memory space and the like in an existing mining algorithm. According to the improved Prefixspan algorithm-based radar data frequent pattern mining method, an improved algorithm adopts a bitmap thought; a chain storage structure is designed; and a support degree number of a frequent 1-item set and the positions of items in a sequence are stored during data reading, so that the problems of memory deficiency of a Span algorithm during mining of a large amount of data sets, two-time scanning of the database in a Prefixspan algorithm and construction of a large amount of projection databases in a mining process are effectively solved, and the radar signal data frequent pattern mining can be better realized. Mined frequent patterns are used for constructing apattern library; the method can be used for analyzing radar pattern cycle and early warning; and by performing time verification analysis on the patterns, an association relationship among events canbe obtained.

Description

technical field [0001] A radar data frequent pattern mining method based on the improved Prefixspan algorithm, which is applied to the establishment of the pattern library in the radar data, analysis of the pattern period, pattern early warning, etc. At the same time, through the time verification analysis of the pattern, the correlation relationship between events can be obtained . It specifically involves technologies such as division of data blocks, mapping of sequences, and frequent pattern mining. Background technique [0002] Data mining technology can be extended to many aspects. Sequential pattern mining based on association rules is a research branch with great application value, and it is also widely used in various industries. For example, in commercial marketing, sequential pattern mining is used to study customers' buying habits and reasonable placement of items to increase sales. "Beer and diapers" is the marketing pattern discovered from it; in biology, seque...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/26
Inventor 屈鸿曾志符明晟刘金凤刘昕彤樊珍
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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