Maximum Complex Task Assignment: Towards Tasks Correlation in Spatial Crowdsourcing

Authors:
Hung Dang;Tuan Nguyen;Hien To
Affiliations:
University of Information Technology, KM20 Hanoi Hwy, Thu Duc, HCMC, Vietnam;University of Information Technology, KM20 Hanoi Hwy, Thu Duc, HCMC, Vietnam;University of Southern California, SL 300, Los Angeles, CA 90089-0781, USA
Venue:
Proceedings of International Conference on Information Integration and Web-based Applications & Services
Year:
2013

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Abstract

Spatial crowdsourcing has gained emerging interest from both research communities and industries. Most of current spatial crowdsourcing frameworks assume independent and atomic tasks. However, there could be some cases that one needs to crowdsource a spatial complex task which consists of some spatial sub-tasks (i.e., tasks related to a specific location). The spatial complex task's assignment requires assignments of all of its sub-tasks. The currently available frameworks are inapplicable to such kind of tasks. In this paper, we introduce a novel approach to crowdsource spatial complex tasks. We first formally define the Maximum Complex Task Assignment (MCTA) problem and propose alternative solutions. Subsequently, we perform various experiments using both real and synthetic datasets to investigate and verify the usability of our proposed approach.