Towards City-scale Mobile Crowdsourcing: Task Recommendations under Trajectory Uncertainties

• Main Authors: CHEN CEN, CHENG, Shih-Fen, LAU, Hoong Chuin, MISRA, Archan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Deterministic modeling; Industry practices; Integer linear program; sLagrangian relaxation techniques; Location based; Mobile crowdsourcing; Stochastic task; Transportation network; Computer Sciences; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/2815; https://ink.library.smu.edu.sg/context/sis_research/article/3815/viewcontent/IJCAI2015_City_scaleCrowdsourcing.pdf
• Institution: Singapore Management University

In this work, we investigate the problem of large-scale mobile crowdsourcing, where workers are financially motivated to perform location-based tasks physically. Unlike current industry practice that relies on workers to manually pick tasks to perform, we automatically make task recommendation based...