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Method for intelligently identifying data content and generating corresponding industry report

A technology for data content and intelligent identification, applied in special data processing applications, other database retrieval, other database clustering/classification, etc. The effect of artificial consumption

Inactive Publication Date: 2020-05-19
BEIJING YONGHONG SHANGZHI TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the process of selecting charts, the people who view the report also need to participate. The process is more labor-intensive and time-consuming, and the cycle is often longer

Method used

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  • Method for intelligently identifying data content and generating corresponding industry report
  • Method for intelligently identifying data content and generating corresponding industry report
  • Method for intelligently identifying data content and generating corresponding industry report

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Experimental program
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Embodiment

[0045] The data model adopts the logistic regression model. The core of the regression method is to find the most suitable parameters for the function, so that the value of the function is closest to the value of the sample. For example, there are two types of data, each consisting of 100 points. When these points are drawn, there will be a line to distinguish the two groups of data. Fitting this curve (because it is likely to be non-linear) is regression. Find this line through a large amount of data, and fit the expression of this line, and then have new data, use this line as a distinction to achieve classification.

[0046] The fitting function hypothesis of logistic regression model among the present invention is h θ (x) = θ 0 +θ 1 x 1 +θ 2 x 2 +…+θ n x n , x 1 ,x 2 ,x 3 ,...,x n are the n eigenvalues ​​of the training samples selected in the learning data set, set n=5,. In order to compress the difference between "sample y(x)-y(fitting)" to a range of 0 to 1,...

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Abstract

The invention discloses a method for intelligently identifying data content and generating a corresponding industry report, and relates to machine learning (ML). The method comprises the steps of bigdata collection, data preparation, data modeling, model training, model evaluation and parameter adjustment, wherein the established model is trained and subjected to parameter optimization through machine learning, an intelligent report model is established, and the model automatically converts a collected and input data set into a visual report according to a learning result. Through the machinelearning technology, tedious report making work is solved, through machine learning, common visual graphs for data display in all industries and corresponding field matching relations are continuously enhanced, reports can be intelligently made according to the data, and a large amount of labor is saved.

Description

technical field [0001] The invention relates to the technical field of business intelligence platforms, and more specifically relates to a method for intelligently identifying data content and generating corresponding industry reports. Background technique [0002] At present, reports in various industries mainly rely on personnel to sort out. For example, a bank needs to make a monthly report, which involves a lot of data and is associated with multiple data sets. When making a report, business personnel must first understand what needs to be displayed. What data needs to be displayed in what way or chart? After this step is completed, it is necessary to consider how to set and match the colors and how to layout the report, so it is quite labor-intensive and the accuracy cannot be guaranteed. [0003] Machine learning has been widely used in various industries, such as intelligent robots, game AI, image recognition, etc. At present, although agile business intelligence (BI...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/904G06F16/906G06N20/00
CPCG06F16/904G06F16/906G06N20/00
Inventor 不公告发明人
Owner BEIJING YONGHONG SHANGZHI TECH