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. Links: http://dl.acm.org/citation.cfm?id=2539243 http://dl.acm.org/citation.cfm?id=2539243 http://dl.acm.org/citation.cfm?doid=2539150.2539243

1. Maximum Complex Task
Assignment
Hien To
hto@usc.edu

2. Geo Crowd Overview
• Geo Task that Leyla defined in ACMGIS paper is
independent, atomic, and thus, simple task.
• What if a situation requires a correlation between
some tasks?
• Basic correlation: Some tasks are required to be
completed together for the aggregation of their
result.
• Keyword: Information Aggregation, Complex Geo
Task

3. Complex Task
• A Spatial Complex Task t of a form <L, Q, S, δ> is a
set of queries Q to be answered at a set of location L
(|L| = |Q|). Simply put, each q of Q is to be answered
as l of L. A set of Q is asked at time s and will be
expired at s+ δ.
• A Spatial Complex Task t is considered to be completed
if and only if ALL q of Q ARE ANSWERED.
• Our optimal goals are to maximize #Complex Task, not
#Subtasks

4. New Constrain
New constrain added to the network flow
problem:
• Lower bound on edges capacity (to enforce
concept of all-or-non subtasks assignment)
• Node demand (to treat all complex task equally no
matter how many subtasks they have)
=> Could be solved by extension of
MaxFLow algorithms

5. Proposed Solution

6. References
• Dang, Hung, Tuan Nguyen, and Hien To. Maximum Complex Task
Assignment: Towards Tasks Correlation in Spatial
Crowdsourcing. In Proceedings of the 15th International Conference
on Information Integration and Web-based Applications & Services
(iiWAS 2013) (Acceptance rate ~30%) (Paper) (Code)

7. References
• Dang, Hung, Tuan Nguyen, and Hien To. Maximum Complex Task
Assignment: Towards Tasks Correlation in Spatial
Crowdsourcing. In Proceedings of the 15th International Conference
on Information Integration and Web-based Applications & Services
(iiWAS 2013) (Acceptance rate ~30%) (Paper) (Code)