Existing Research Static Scenarios: considered as the offline maximum weighted bipartite graph matching problem A crowd worker A spatial task 5 3 Weight: the utility 9 score between a task and a worker 2 Finding a matching to maximize the total utility L. Kazemi et al. Geocrowd: enabling query answering with spatial crowdsourcing In GIS 2012. H. To et al. A server-assigned spatial crowdsourcing framework. In TASA 2015
⚫ Static Scenarios: considered as the offline maximum weighted bipartite graph matching problem. Existing Research L. Kazemi et al. Geocrowd: enabling query answering with spatial crowdsourcing. In GIS 2012. H. To et al. A server-assigned spatial crowdsourcing framework. In TASA 2015. A spatial task A crowd worker 3 5 7 9 2 1 11 6 7 Weight: the utility score between a task and a worker. Finding a matching to maximize the total utility 9
Existing Research Dynamic Scenarios considered as the online maximum weighted bipartite graph matching problem Y Tong et al. Online Mobile Micro-Task Allocation in Spatial Crowdsourcing In ICDE 2016
⚫ Dynamic Scenarios : considered as the online maximum weighted bipartite graph matching problem. Existing Research Y. Tong et al. Online Mobile Micro-Task Allocation in Spatial Crowdsourcing. In ICDE 2016. 10
Offline v.s. Online 5 1 2 2 The offline optimal cost is 20 Offline scenario
Offline v.s. Online Offline Scenario 3 5 7 9 2 1 11 6 7 The offline optimal cost is 20 11
Offline v.s. Online 5 1 2 2 The offline optimal cost is 20 Offline scenario Online Scenario
The offline optimal cost is 20 Offline Scenario Online Scenario 3 5 7 9 2 1 11 6 7 Offline v.s. Online 12
Offline v.s. Online 5 1 1 2 1. Full bipartite graph cannot u be known 2. The new arrival object needs to be immediately assigned based on partial information 2 The offline optimal cost is 20 Offline scenario Online Scenario
Offline Scenario 3 1. Full bipartite graph cannot be known. 2. The new arrival object needs to be immediately assigned based on partial information. 3 5 7 9 2 1 11 6 7 Offline v.s. Online The offline optimal cost is 20 Online Scenario 13