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Tuple granularity-based individual big data pricing method

A technology of big data and tuples, applied in the field of big data, can solve the problem that useful private data cannot be accessed by stakeholders

Inactive Publication Date: 2018-04-17
成都大征创智科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to related issues such as privacy, a large amount of potentially useful private data cannot be accessed by stakeholders

Method used

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  • Tuple granularity-based individual big data pricing method
  • Tuple granularity-based individual big data pricing method
  • Tuple granularity-based individual big data pricing method

Examples

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Embodiment Construction

[0025] According to the above description and acquisition of the characteristic quantity of the price of the personal big data data tuple, the present invention verifies the correctness and effectiveness of the pricing method through a specific example, and the steps are as follows:

[0026] 1) Assume that the trading platform has a data packet, which contains 10 data tuples, and each data tuple has 5 data items. Assume that the cost of collecting, analyzing and sharing this data package is 20 yuan, and the demand price of this data package is 60 yuan. The details of this data package are shown in Table 1;

[0027] 2) According to the assumption of step 1) and the following formula, the supply price P of the data package can be obtained S :

[0028] P S =P D -C

[0029] Among them, P D is the demand price of the data package, and C is the cost of collecting, analyzing and sharing the data package on the trading platform, so the supply price of the data package can be obta...

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Abstract

The invention discloses a personal big data pricing method based on tuple granularity. First, investigate the data attributes that affect the value of data, and then analyze the influence of factors such as information entropy, value weight, data reference index, and data cost on the value of data tuples, and derive a value calculation method for data tuples, which can be based on Parameters are dynamically adjusted. With the increase of data scale, reduction of data cost and improvement of data quality, all parties in data transactions will get more benefits. Finally, a concrete example is used to verify the correctness and validity of the pricing method.

Description

Technical field [0001] The invention relates to the technical field of big data, in particular to a personal big data pricing method based on tuple granularity. Background technique [0002] With the huge value of big data being re-recognized and the cost of computer storage falling, the amount of personal information collected has reached an unprecedented level. The economic value of this data justifies the success that many Internet companies have achieved from search engines, social media sites, and selling this information. However, due to related issues such as privacy, a large amount of potentially useful private data cannot be accessed by stakeholders. [0003] Personal big data is of great value in itself, both for the data owner and the organization attempting to analyze it. Generally, personal big data refers to characteristic behavioral data involving personal privacy, which is generated in personal life activities or work, and can be owned or controlled by indi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02
CPCG06Q30/0283
Inventor 郭兵沈艳申云成曹亚波段旭良张洪董祥千黄义纯王丹张鹏博
Owner 成都大征创智科技有限公司
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