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Crowdsourcing systems on the World-Wide Web
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Human-assisted graph search: it's okay to ask questions
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Guess who?: enriching the social graph through a crowdsourcing game
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Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
A privacy-aware framework for participatory sensing
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Proceedings of the 12th International ACM Workshop on Data Engineering for Wireless and Mobile Acess
GeoTruCrowd: trustworthy query answering with spatial crowdsourcing
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Maximizing the number of worker's self-selected tasks in spatial crowdsourcing
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Mobility and social networking: a data management perspective
Proceedings of the VLDB Endowment
Maximum Complex Task Assignment: Towards Tasks Correlation in Spatial Crowdsourcing
Proceedings of International Conference on Information Integration and Web-based Applications & Services
MediaQ: mobile multimedia management system
Proceedings of the 5th ACM Multimedia Systems Conference
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With the ubiquity of mobile devices, spatial crowdsourcing is emerging as a new platform, enabling spatial tasks (i.e., tasks related to a location) assigned to and performed by human workers. In this paper, for the first time we introduce a taxonomy for spatial crowdsourcing. Subsequently, we focus on one class of this taxonomy, in which workers send their locations to a centralized server and thereafter the server assigns to every worker his nearby tasks with the objective of maximizing the overall number of assigned tasks. We formally define this maximum task assignment (or MTA) problem in spatial crowdsourcing, and identify its challenges. We propose alternative solutions to address these challenges by exploiting the spatial properties of the problem space. Finally, our experimental evaluations on both real-world and synthetic data verify the applicability of our proposed approaches and compare them by measuring both the number of assigned tasks and the travel cost of the workers.