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Index correlation analysis method

A correlation analysis and index technology, applied in the field of data processing, can solve problems such as inability to visually display associated data and low processing efficiency

Pending Publication Date: 2021-09-17
SENSOR NETWORKS TECH BEIJING CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, in related technologies, as long as the association analysis is for data mining, it cannot visually display the associated data, resulting in relatively low efficiency of subsequent processing

Method used

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Embodiment Construction

[0045] In order to more clearly understand the above objects, features and advantages of the present disclosure, the solutions of the present disclosure will be further described below. It should be noted that, in the case of no conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other.

[0046] In the following description, many specific details are set forth in order to fully understand the present disclosure, but the present disclosure can also be implemented in other ways than described here; obviously, the embodiments in the description are only some of the embodiments of the present disclosure, and Not all examples.

[0047] At present, the association analysis model widely cited in enterprises is a very useful data mining model, which can help enterprises to make many useful product combination recommendations, preferential promotion combinations, and at the same time can guide whether the shelf placement is ...

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Abstract

The invention relates to an index correlation analysis method, and relates to the technical field of data processing; the method comprises the steps: obtaining a target index of an object in a selected time range; calculating the degree of association between the target index and each index; the correlation degree comprises positive correlation and negative correlation; obtaining a preset number of association indexes according to the association degree and a preset threshold value; ranking the association indexes from high to low according to the association degrees, and dividing the preset number of association indexes into N areas to be displayed according to the sorting result, wherein the association indexes displayed in the first N-1 areas comprise index names and sorting serial numbers, and the association indexes displayed in the last area are distributed in a point shape, and wherein the sizes of the index names and the sorting serial numbers are in direct proportion to the association degree. Therefore, the relevance between the target index and the association index can be simply and intuitively obtained, so that when the data is abnormal, the reason of the data abnormality can be analyzed through the change of the strongly associated association index, and the business strategy is appointed in combination with the core index.

Description

technical field [0001] The present disclosure relates to the technical field of data processing, and in particular to an index correlation analysis method. Background technique [0002] At present, correlation analysis has been widely used in precision marketing in the e-commerce industry, such as product recommendation, launching promotional gift packages or preferential package packages. [0003] However, in related technologies, as long as the association analysis is performed for data mining, it cannot visually display the associated data, resulting in relatively low efficiency of subsequent processing. Contents of the invention [0004] In order to solve the above technical problem or at least partly solve the above technical problem, the present disclosure provides an index correlation analysis method. [0005] The present disclosure provides an index correlation analysis method, including: [0006] Get target metrics for objects in the selected timeframe; [0007...

Claims

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Application Information

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IPC IPC(8): G06Q30/02
CPCG06Q30/0201
Inventor 桑文锋刘耀洲曹犟付力力安志远岳帅胡士文李笑宁
Owner SENSOR NETWORKS TECH BEIJING CO LTD
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