Fair data pricing based on data quality

Siying CHEN; Dan ZHANG; Xiaoou DING; Hongzhi WANG

doi:10.11959/j.issn.2096-0271.2024025

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Fair data pricing based on data quality

DATA ASSETIZATION TECHNOLOGY | 更新时间：2024-06-03

- Fair data pricing based on data quality
- Big data research Vol. 10, Issue 2, Pages: 54-67(2024)
- 作者机构：
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- DOI：10.11959/j.issn.2096-0271.2024025
  CLC： TP311
- Online First：2024-03，
  
  Published：15 March 2024
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Siying CHEN, Dan ZHANG, Xiaoou DING, et al. Fair data pricing based on data quality[J]. Big data research, 2024, 10(2): 54-67.
DOI：

Siying CHEN, Dan ZHANG, Xiaoou DING, et al. Fair data pricing based on data quality[J]. Big data research, 2024, 10(2): 54-67. DOI： 10.11959/j.issn.2096-0271.2024025.

摘要

随着数据的爆炸式增长，以数据为关键要素的数字经济进一步发展。在数据市场中，建立公平高效的定价交易系统变得尤为重要。针对数据市场的公平性，提出了基于数据质量的数据市场模型。首先，以用户的需求为目标，制定综合数据质量的定价策略。其次，为防止用户的恶意欺诈行为，设计了保障公平数据交易的市场机制。最后，在原始数据交易的基础上，讨论了与数据质量相关的数据清洗服务，通过游戏理论中的机制设计多用户清洗价值分配机制。通过实验证明了按照模型构建系统的效率和有效性，可以保证数据市场的公平性。

Abstract

With the explosive growth of data

the digital economy

where data serves as a crucial element

continues to advance.In the context of data markets

establishing a fair and efficient pricing and trading system becomes paramount.Addressing fairness within data markets

this study introduces a data market model based on data quality.Firstly

aiming at user demands

a comprehensive pricing strategy based on data quality is formulated.Secondly

to mitigate malicious fraudulent behaviors from users

a market mechanism ensuring fair data transactions is designed.Lastly

building upon primary data transactions

data cleaning services related to data quality are discussed.A multi-user value allocation mechanism for cleaning is designed using principles from game theory.Experimental results demonstrate that constructing systems according to this model ensures both efficiency and fairness within data markets.

关键词

Keywords

references

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