ul Hassan, Umair and Curry, Edward
(2015)
Flag-Verify-Fix: Adaptive Spatial Crowdsourcing
leveraging Location-based Social Networks.
In: SIGSPATIAL '15: Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, November 2015, Bellevue, WA, USA.
Abstract
This paper introduces the flag-verify-fix pattern that employs spatial
crowdsourcing for city maintenance. The patterns motivates the
need for appropriate assignment of dynamically arriving spatial
tasks to a pool for workers on the ground. The assignment is
aimed at maximizing the coverage of tasks spread over spatial
locations; however, the coverage depends of willingness of workers
to perform tasks assigned to them. We introduce the maximum
coverage assignment problem that formulates two design issues of
dynamic assignment. The quantity issue determines the number of
worker required for a task and selection issue determines the set
of workers. We propose an adaptive algorithm that uses location
diversity based on a location-based social network to address the
quantity issue and employs Thompson sampling for selecting the
workers by learning their willingness. We evaluate the performance
of the proposed algorithm in terms of coverage and number of
assignments using real world datasets. The results show that our
proposed algorithm achieves 30%-50% more coverage than the
baseline algorithms, while requiring less workers per task.
| Item Type: |
Conference or Workshop Item
(Paper)
|
| Keywords: |
Spatial crowdsourcing; location diversity; multi-armed bandit; |
| Academic Unit: |
Faculty of Social Sciences > School of Business |
| Item ID: |
16011 |
| Identification Number: |
https://doi.org/10.1145/2820783.2820870 |
| Depositing User: |
Souleiman Hasan
|
| Date Deposited: |
30 May 2022 11:51 |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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