Mass data association relationship analysis method, device and system

A related relationship and mass data technology, applied in the computer field, can solve problems such as large errors in prediction and analysis results, and achieve the effect of increasing the amount of sample data and improving accuracy

Pending Publication Date: 2019-05-24
INSPUR QILU SOFTWARE IND
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  • Application Information

AI Technical Summary

Problems solved by technology

Due to the size of the sample data, the error

Method used

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  • Mass data association relationship analysis method, device and system
  • Mass data association relationship analysis method, device and system
  • Mass data association relationship analysis method, device and system

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Embodiment Construction

[0035] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work belong to the protection of the present invention. scope.

[0036] Such as figure 1 As shown, the embodiment of the present invention provides a method for analyzing the association relationship of massive data, which may include the following steps:

[0037] Step 101: Use the data collection tool to collect the data stored in the massive database in real time, and send the collected data to the message channel in

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Abstract

The invention provides a mass data association relationship analysis method, device and system, and the method comprises the steps: employing a data collection tool to collect data stored in a mass database in real time, and sending the collected data to a message channel in real time; Carrying out real-time data cleaning processing on the data output by the message channel to obtain cleaned data;And performing association relationship analysis on the cleaned data by utilizing a related algorithm in a machine learning library built in a streaming real-time computing framework to obtain an association relationship analysis result. Based on a streaming computing framework, by means of a machine learning library and a built-in algorithm of the streaming computing framework, the real-time analysis task of the incidence relation of the hundred million-level mass data sets can be efficiently completed. As the sample data volume is greatly increased and is not limited, the scheme can improvethe data analysis accuracy.

Description

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Claims

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Application Information

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Owner INSPUR QILU SOFTWARE IND
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