AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Tsinghua Science and Technology Article
PDF (706.4 KB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

A Pricing Model for Big Personal Data

Yuncheng Shen, Bing Guo( ), Yan Shen( ), Xuliang Duan, Xiangqian Dong, Hong Zhang
College of Computer Science, Sichuan University, Chengdu 610065, China.
College of Information Science and Technology, Zhaotong University, Zhaotong 657000, China.
School of Control Engineering, Chengdu University of Information Technology, Chengdu 610225, China.
Show Author Information

Abstract

Big Personal Data is growing explosively. Consequently, an increasing number of internet users are drowning in a sea of data. Big Personal Data has enormous commercial value; it is a new kind of data asset. An urgent problem has thus arisen in the data market: How to price Big Personal Data fairly and reasonably. This paper proposes a pricing model for Big Personal Data based on tuple granularity, with the help of comparative analysis of existing data pricing models and strategies. This model is put forward to implement positive rating and reverse pricing for Big Personal Data by investigating data attributes that affect data value, and analyzing how the value of data tuples varies with information entropy, weight value, data reference index, cost, and other factors. The model can be adjusted dynamically according to these parameters. With increases in data scale, reductions in its cost, and improvements in its quality, Big Personal Data users can thereby obtain greater benefits.

Keywords

data tupleBig Personal Datapositive gradingreverse pricingpricing model

References

[1]
Haddadi H., Mortier R., and Hand S., Privacy analytics, ACM SIGCOMM Computer Communication Review, vol. 42, no. 2, pp. 94-98, 2012.
Crossref Google Scholar
[2]
Moiso C. and Minerva R., Towards a user-centric personal data ecosystem, in Proc. 16th Conf. on Intelligence in Next Generation Networks, Berlin, Germany, 2012, pp. 202-209.
[3]
Fung B. C. M., Wang K., Chen R., and Yu P. S., Privacy-preserving data publishing: A survey of recent developments, ACM Comput. Surv., vol. 42, no. 4, pp. 2623-2627, 2010.
Crossref Google Scholar
[4]
Ng I. C. L. and Ho S. Y., Creating New Markets in the Digital Economy: Value and Worth. Cambridge University Press, 2014.
[5]
Muschalle A., Stahl F., Löser A., and Vossen G., Pricing approaches for data markets, in Enabling Real-Time Business Intelligence, Castellanos M., Dayal U., and Rundensteiner E. A., eds. Springer Berlin Heidelberg, 2013, pp. 129-144.
Crossref
[6]
Balazinska M., Howe B., and Suciu D., Data markets in the cloud: An opportunity for the database community, Proceedings of the VLDB Endowment, vol. 4, no. 12, pp. 1482-1485, 2011.
Crossref Google Scholar
[7]
Shapiro C. and Varian H. R., Versioning: The smart way to sell information, Harvard Business Review, vol. 76, pp. 107-115, 1998.
Google Scholar
[8]
Koutris P., Upadhyaya P., Balazinska M., Howe B., and Suciu D., Query-based data pricing, ACM Transactions on Database Systems, vol. 27, no. 4, pp. 438-493, 2012.
Crossref Google Scholar
[9]
Tang R., Wu H., Bao Z., Bressan S. E., and Valduriez P., The price is right: Models and algorithms for pricing data, Lecture Notes in Computer Science, vol. 8056, no. 2, pp. 380-394, 2013.
Crossref Google Scholar
[10]
Balazinska M., Howe B., Koutris P., Dan S., and Upadhyaya P., A discussion on pricing relational data, Lecture Notes in Computer Science, vol. 8000, pp. 167-173, 2013.
Crossref Google Scholar
[11]
Gkatzelis V., Aperjis C., and Huberman B. A., Pricing private data, Social Science Electronic Publishing, vol. 60, no. 5, pp. 1249-1257, 2012.
Crossref Google Scholar
[12]
Riederer C., Erramilli V., Chaintreau A., Krishnamurthy B., and Rodriguez P., For sale: your data: by: you, in Proceedings of the 10th ACM Workshop on Hot Topics in Networks, 2011, pp. 1-6.
Crossref
[13]
Li C., Li D. Y., Miklau G., and Suciu D., A theory of pricing private data, in Proceedings of the 16th International Conference on Database Theory, 2013, pp. 33-44.
Crossref
[14]
Acquisti A., John L., and George L., What is privacy worth? Journal of Legal Studies, vol. 42, no. 2, pp. 249-274, 2009.
Crossref Google Scholar
[15]
Moody D. L. and Walsh P., Measuring the value of information—An asset valuation approach, presented at European Conference on Information Systems, Ecis 1999, Copenhagen, Denmark, 1999.
[16]
Sun H., Tu Q. W., and Wang X. W., Pricing of SaaS in cloud computing based on mathematical models, (in Chinese), Journal of Shanghai University of Science and Technology, vol. 36, no. 2, pp. 199-204, 2014.
Google Scholar
[17]
Jang D., Information Theory and Coding, (in Chinese). Electronic Industry Press, 2013.
Tsinghua Science and Technology
Volume 21 Issue 5,
October 2016
Pages 482-490
DOI: 10.1109/TST.2016.7590317
Cite this article:
Shen Y, Guo B, Shen Y, et al. A Pricing Model for Big Personal Data. Tsinghua Science and Technology, 2016, 21(5): 482-490. https://doi.org/10.1109/TST.2016.7590317

551

Views

27

Downloads

42

Crossref

N/A

Web of Science

49

Scopus

1

CSCD

Altmetrics
Received: 23 July 2016
Revised: 03 August 2016
Accepted: 22 August 2016
Published: 18 October 2016
© The author(s) 2016
Return