A method and system for identifying similar objects based on big data
An object recognition and big data technology, applied in database update, digital data processing, structured data retrieval, etc., can solve problems such as difficult to meet needs, too much suspected data, and difficult to filter, so as to reduce the pressure of later verification and reduce suspected The effect of matching data and reducing time spent
Active Publication Date: 2021-09-03
YANTAI HAIYI SOFTWARE
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Problems solved by technology
When using the traditional precise location-based track matching method for identification, there are often problems such as time-consuming, too much suspected data, and difficult to filter, especially in today's situation of geometric growth of data volume, the traditional method is based on the limitations of localized centralized calculation Increasingly prominent, increasingly difficult to meet needs
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[0046] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0047] The track similar object recognition system based on big data of the present invention includes a spatial normalization module for discretizing track dictionary data and generating a track identification dictionary, and a data sorting module for data preparation, data filtering and cleaning, and data standardization , the spatial point sequence generation module used to integrate objects and serialize the track point data of each object according to the evolution of spatial position over time, the behavior track sequence extraction module used to extract and serialize behavior tracks, The behavior matrix generation module used to integrate the object data to be analyzed with all the data and construct the behavior calculation matrix, the behavior matrix ope...
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The invention belongs to the field of data analysis, and relates to a method and system for identifying similar objects based on big data. The present invention uses the spatial normalization module, the data sorting module, the spatial point sequence generation module, the behavior track sequence extraction module, the behavior matrix generation module, and the behavior matrix operation module to connect in sequence to construct a track identification dictionary for the original data of track positions; Identify the dictionary to standardize the incoming data; integrate the track point data belonging to each object; construct the track point sequence of each object in the time window; generate the displacement track sequence for the track point sequence of each object; construct the behavior calculation matrix To calculate the trajectory similarity; output the result that the behavior similarity meets the conditions. The present invention obtains and analyzes the spatial position movement information of different objects and uses an algorithm to calculate the similarity between the spatial position changes of different objects, explores the similarity relationship between objects, and identifies and searches for objects and groups with similar behaviors.
Description
technical field [0001] The invention belongs to the technical field of data analysis, in particular to the technical field of behavioral similarity data analysis, and in particular to a method and system for identifying similar objects based on big data. Background technique [0002] In the fields of e-commerce and public security, it is hoped that by analyzing the data collected by a large number of data collection devices scattered around or the network nodes visited by users, it is hoped to find objects with similar behaviors to the target person or group. When using the traditional precise location-based track matching method for identification, there are often problems such as time-consuming, too much suspected data, and difficult to filter, especially in today's situation of geometric growth of data volume, the traditional method is based on the limitations of localized centralized calculation Increasingly prominent, it is becoming more and more difficult to meet the n...
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IPC IPC(8): G06F16/215G06F16/23G06F16/2458
Inventor 于瑞强王林刘伯栋翟特刘波杜星学徐婧李经帅
Owner YANTAI HAIYI SOFTWARE