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Task assignment in spatial crowdsourcing: challenges and approaches
| Content Provider | ACM Digital Library |
|---|---|
| Author | To, Hien |
| Abstract | Spatial crowdsourcing (a.k.a mobile crowdsourcing) is a new paradigm of data collection, which has been emerged in the last few years to enable workers to perform tasks in the physical world. The objective of spatial crowdsourcing is to outsource a set of location-specific tasks to a set of workers, in which the workers are required to physically be at the task locations to complete them, i.e., taking pictures or collecting air quality information at specified locations of interest. In this paper, we discuss the unique challenges of spatial crowdsourcing: task assignment, incentive mechanism, worker's location privacy and the absence of real-world datasets. Thereafter, we present our current approaches to those issues. |
| Starting Page | 1 |
| Ending Page | 4 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450345842 |
| DOI | 10.1145/3003819.3003820 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-10-31 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
