Journal
PROCEEDINGS OF THE VLDB ENDOWMENT
Volume 6, Issue 12, Pages 1198-1201Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.14778/2536274.2536275
Keywords
-
Funding
- Australian Research Council (ARC) [FT120100832]
Ask authors/readers for more resources
Destination prediction is an essential task for a number of emerging location based applications such as recommending sightseeing places and sending targeted advertisements. A common approach to destination prediction is to derive the probability of a location being the destination based on historical trajectories. However, existing techniques suffer from the data sparsity problem, i.e., the number of available historical trajectories is far from sufficient to cover all possible trajectories. This problem considerably limits the amount of query trajectories whose predicted destinations can be inferred. In this demonstration, we showcase a system named DesTeller that is interactive, user-friendly, publicly accessible, and capable of answering real-time queries. The underlying algorithm Sub-Trajectory Synthesis (SubSyn) successfully addressed the data sparsity problem and is able to predict destinations for almost every query submitted by travellers. We also consider the privacy protection issue in case an adversary uses SubSyn algorithm to derive sensitive location information of users.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available