In this project, we derived 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. Additionally, two example scenarios are investigated: the delivery of targeted ads specific to a user’s home location and the estimation of traffic state. In both cases, the methodology leads to quantifiably better purchasing decisions than competing methods.
Publications:
“On the Value of Spatiotemporal Information: Principles and Scenarios”
Heba Aly, John Krumm, Gireeja Ranade and Eric Horvitz
ACM SIGSPATIAL, 2018
- Acceptance Rate: 20%
- Best Paper Runner Up