Crime big data point mode analysis method based on F function and improved KD tree

A pattern analysis, KD tree technology, applied in the direction of electrical digital data processing, character and pattern recognition, digital data information retrieval, etc., can solve the problems of long computing time, waste of resources, low efficiency, etc. Complex computing problems and the effect of improving the utilization of computing resources

Inactive Publication Date: 2019-07-02
WUHAN UNIV
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Problems solved by technology

In the face of today's massive amount of criminal raw data, the traditional traversal search method needs to calculate the distance between the center point and all poin

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  • Crime big data point mode analysis method based on F function and improved KD tree
  • Crime big data point mode analysis method based on F function and improved KD tree
  • Crime big data point mode analysis method based on F function and improved KD tree

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[0018] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0019] Based on the nearest neighbor distance algorithm F function in the spatial point pattern analysis method, the nearest neighbor points of all crime points are required when analyzing the spatial distribution pattern of criminal events. The traditional traversal search mode needs to follow a certain order and systematically access a data structure. All the elements of , this search method is only applicable to the case of small amount of data, and when the amount of data is large, there will be problems of long calculation time and low calculation efficie...

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Abstract

The invention discloses a crime big data point mode analysis method based on an F function and improved KD tree parallel computing. The invention provides a method capable of rapidly analyzing a crimespace distribution mode, namely a crime big data point mode analysis method based on an F function and improved KD tree parallel computing, by combining improved KD tree parallel computing with a nearest neighbor distance point mode analysis method (F function) according to the demand of current crime big data processing. According to the method, the criminal point events in the space are clustered to construct the KD tree, and the nearest neighbor distance of the criminal point events in each KD tree is calculated in parallel, so that the effect of integrating the KD tree into scattered andpartitioned parallel processing is achieved, the calculation efficiency is improved, and the utilization rate of calculation resources is increased.

Description

technical field [0001] The invention belongs to the field of big data mining, and relates to a method for analyzing patterns of big data points of crimes, in particular to a method for analyzing patterns of big data points of crimes based on F function and improved KD tree parallel calculation. Background technique [0002] With the development of Internet technology, the world today has entered the era of big data. Big data is a collection of massive related data in form, and generally refers to the ability to collect and analyze a large amount of information in practical applications. In the past ten years, the informatization construction of public security organs has made rapid progress. A public security informatization network has been established vertically to the bottom and horizontally to the edge. All police businesses have fully realized informatization management and accumulated massive basic business data. Among them, the large and scattered amount of criminal ...

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Application Information

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IPC IPC(8): G06F16/2458G06K9/62G06Q50/26
CPCG06Q50/265G06F18/24147G06F18/24323
Inventor 何雨情杨立涛白璐斌黄舒哲
Owner WUHAN UNIV
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