Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article

To Buy or Not to Buy: Computing Value of Spatiotemporal Information

Published: 12 September 2019 Publication History

Abstract

Location data from mobile devices is a sensitive yet valuable commodity for location-based services and advertising. We investigate the intrinsic value of location data in the context of strong privacy, where location information is only available from end users via purchase. We present an algorithm to compute the expected value of location data from a user, without access to the specific coordinates of the location data point. We use decision-theoretic techniques to provide a principled way for a potential buyer to make purchasing decisions about private user location data. We illustrate our approach in three scenarios: the delivery of targeted ads specific to a user’s home location, the estimation of traffic speed, and location prediction. In all three cases, the methodology leads to quantifiably better purchasing decisions than competing methods.

References

[1]
Eytan Adar and Bernardo A. Huberman. 2001. A market for secrets. First Monday 6, 8 (2001).
[2]
Heba Aly, John Krumm, Gireeja Ranade, and Eric Horvitz. 2018. On the value of spatiotemporal information: Principles and scenarios. In Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. ACM, 179--188.
[3]
Daniel Ashbrook and Thad Starner. 2003. Using GPS to learn significant locations and predict movement across multiple users. Personal and Ubiquitous Computing 7, 5 (2003), 275--286.
[4]
Howard Beales. 2010. The value of behavioral targeting. Network Advertising Initiative 1 (2010).
[5]
Anna Marie Chang, Alison C. Leung, Olivia Saynisch, Heather Griffis, Shawndra Hill, John C. Hershey, Lance B. Becker, David A. Asch, Ariel Seidman, and Raina Martha Merchant. 2014. Using a mobile app and mobile workforce to validate data about emergency public health resources. Emergency Medicine Journal 31, 7 (2014), 545--548.
[6]
Puget Sound Regional Council. 2016. Travel Surveys: Spring 2015 Household Survey. Retrieved on 5 September, 2019 from https://www.psrc.org/travel-surveys-2015-household-survey.
[7]
Dan Cvrcek, Marek Kumpost, Vashek Matyas, and George Danezis. 2006. A study on the value of location privacy. In Proceedings of the 5th ACM Workshop on Privacy in Electronic Society. ACM, 109--118.
[8]
Frank Van Diggelen. 2007. Update: GNSS accuracy: Lies, damn lies, and statistics. GPS World 18, 1 (2007), 26--33.
[9]
Michael F. Goodchild. 2007. Citizens as sensors: The world of volunteered geography. GeoJournal 69, 4 (2007), 211--221.
[10]
Mohinder S. Grewal. 2011. Kalman filtering. In International Encyclopedia of Statistical Science. Springer, 705--708.
[11]
Mordechai Haklay and Patrick Weber. 2008. Openstreetmap: User-generated street maps. Pervasive Computing 7, 4 (2008), 12--18.
[12]
Manish Jain, Matthew Taylor, Milind Tambe, and Makoto Yokoo. 2009. DCOPs meet the real world: Exploring unknown reward matrices with applications to mobile sensor networks. In 21st International Joint Conference on Artificial Intelligence.
[13]
Yaron Kanza and Hanan Samet. 2015. An online marketplace for geosocial data. In SIGSPATIAL. ACM, 10.
[14]
Leyla Kazemi and Cyrus Shahabi. 2012. Geocrowd: Enabling query answering with spatial crowdsourcing. In Proceedings of the 20th International Conference on Advances in Geographic Information Systems. ACM, 189--198.
[15]
Andreas Krause, Eric Horvitz, Aman Kansal, and Feng Zhao. 2008a. Toward community sensing. In 2008 International Conference on Information Processing in Sensor Networks (IPSN’08). IEEE, 481--492.
[16]
Andreas Krause, Ajit Singh, and Carlos Guestrin. 2008b. Near-optimal sensor placements in Gaussian processes: Theory, efficient algorithms and empirical studies. Journal of Machine Learning Research 9, (Feb. 2008), 235--284.
[17]
John Krumm and Eric Horvitz. 2006. Predestination: Inferring destinations from partial trajectories. In International Conference on Ubiquitous Computing. Springer, 243--260.
[18]
John Krumm, Dany Rouhana, and Ming-Wei Chang. 2015. Placer++: Semantic place labels beyond the visit. In Proceedings of the 2015 IEEE International Conference on Pervasive Computing and Communications (PerCom’15). IEEE, 11--19.
[19]
Juha K. Laurila, Daniel Gatica-Perez, Imad Aad, Olivier Bornet, Trinh-Minh-Tri Do, Olivier Dousse, Julien Eberle, Markus Miettinen, et al. 2012. The mobile data challenge: Big data for mobile computing research. In Pervasive Computing.
[20]
Mingqi Lv, Ling Chen, and Gencai Chen. 2012. Discovering personally semantic places from GPS trajectories. In CIKM. ACM, 1552--1556.
[21]
Trend Micro. 2015. How Much is Your Personal Data Worth? Survey Says… Retrieved on 5 September, 2019 from https://www.trendmicro.com/vinfo/us/security/news/internet-of-things/how-much-is-your-personal-data-worth-survey-says.
[22]
Vipal Monga. 2014. The Big Mystery: What’s Big Data Really Worth? Retrieved on 5 September, 2019 from https://blogs.wsj.com/cfo/2014/10/13/the-big-mystery-whats-big-data-really-worth/.
[23]
D. Warner North. 1968. A tutorial introduction to decision theory. IEEE Transactions on Systems Science and Cybernetics 4, 3 (1968), 200--210.
[24]
U.S. Bureau of Labor Statistics. 2016. American Time Use Survey. Retrieved on 5 September, 2019 from https://www.bls.gov/tus/.
[25]
Joseph Phelps, Glen Nowak, and Elizabeth Ferrell. 2000. Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy 8 Marketing 19, 1 (2000), 27--41.
[26]
Stephen O. Rice. 1945. Mathematical analysis of random noise. The Bell System Technical Journal 24, 1 (1945), 46--156.
[27]
Sambu Seo, Marko Wallat, Thore Graepel, and Klaus Obermayer. 2000. Gaussian process regression: Active data selection and test point rejection. In Mustererkennung 2000. Springer, 27--34.
[28]
Jan Sijbers, Arnold Jan den Dekker, Erik Raman, and Dirk Van Dyck. 1999. Parameter estimation from magnitude MR images. International Journal of Imaging Systems and Technology 10, 2 (1999), 109--114.
[29]
Amarjeet Singh, Andreas Krause, Carlos Guestrin, William J. Kaiser, and Maxim A. Batalin. 2007. Efficient planning of informative paths for multiple robots. In International Joint Conferences on Artificial Intelligence, Vol. 7. 2204--2211.
[30]
Jacopo Staiano, Nuria Oliver, Bruno Lepri, Rodrigo de Oliveira, Michele Caraviello, and Nicu Sebe. 2014. Money walks: A human-centric study on the economics of personal mobile data. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 583--594.
[31]
Emily Steel. 2013. Financial worth of data comes in at under a penny a piece. Retrieved on 5 September, 2019 from https://www.ft.com/content/3cb056c6-d343-11e2-b3ff-00144feab7de.
[32]
George J. Stigler. 1961. The economics of information. Journal of Political Economy 69, 3 (1961), 213--225.
[33]
Catherine E. Tucker. 2012. The economics of advertising and privacy. International Journal of Industrial Organization 30, 3 (2012), 326--329.
[34]
Feng Zhao, Jaewon Shin, and James Reich. 2002. Information-driven dynamic sensor collaboration for tracking applications. IEEE Signal Processing Magazine 19, 2 (2002), 61--72.

Cited By

View all
  • (2023)Addressing budget allocation and revenue allocation in data market environments using an adaptive sampling algorithmProceedings of the 40th International Conference on Machine Learning10.5555/3618408.3620178(42081-42097)Online publication date: 23-Jul-2023
  • (2023)UGCC: Social Media User Geolocation via Cyclic CouplingIEEE Transactions on Big Data10.1109/TBDATA.2023.32429619:4(1128-1141)Online publication date: 1-Aug-2023
  • (2023)Construction of a high-precision general geographical location words datasetComputer Standards & Interfaces10.1016/j.csi.2022.10369284:COnline publication date: 1-Mar-2023
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Spatial Algorithms and Systems
ACM Transactions on Spatial Algorithms and Systems  Volume 5, Issue 4
December 2019
164 pages
ISSN:2374-0353
EISSN:2374-0361
DOI:10.1145/3361970
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 September 2019
Accepted: 01 March 2019
Revised: 01 March 2019
Received: 01 December 2018
Published in TSAS Volume 5, Issue 4

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. GPS
  2. advertising
  3. crowdsourcing
  4. decision theory
  5. location
  6. traffic
  7. value of information (VOI)

Qualifiers

  • Research-article
  • Research
  • Refereed

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)13
  • Downloads (Last 6 weeks)1
Reflects downloads up to 26 Sep 2024

Other Metrics

Citations

Cited By

View all
  • (2023)Addressing budget allocation and revenue allocation in data market environments using an adaptive sampling algorithmProceedings of the 40th International Conference on Machine Learning10.5555/3618408.3620178(42081-42097)Online publication date: 23-Jul-2023
  • (2023)UGCC: Social Media User Geolocation via Cyclic CouplingIEEE Transactions on Big Data10.1109/TBDATA.2023.32429619:4(1128-1141)Online publication date: 1-Aug-2023
  • (2023)Construction of a high-precision general geographical location words datasetComputer Standards & Interfaces10.1016/j.csi.2022.10369284:COnline publication date: 1-Mar-2023
  • (2021)Solving Last-Mile Logistics Problem in Spatiotemporal Crowdsourcing via Role Awareness With Adaptive ClusteringIEEE Transactions on Computational Social Systems10.1109/TCSS.2021.30512998:3(668-681)Online publication date: Jun-2021
  • (2020)Spatial Privacy PricingProceedings of the 28th International Conference on Advances in Geographic Information Systems10.1145/3397536.3422213(263-272)Online publication date: 3-Nov-2020
  • (2020)An overview of microblog user geolocation methodsInformation Processing & Management10.1016/j.ipm.2020.102375(102375)Online publication date: Aug-2020

View Options

Get Access

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media