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Traccs: Trajectory-Aware Coordinated Urban Crowd-Sourcing, Cen Chen, Shih-Fen Cheng, Aldy Gunawan, Archan Misra, Koustuv Dasgupta, Deepthi Chander
Traccs: Trajectory-Aware Coordinated Urban Crowd-Sourcing, Cen Chen, Shih-Fen Cheng, Aldy Gunawan, Archan Misra, Koustuv Dasgupta, Deepthi Chander
Research Collection School Of Computing and Information Systems
We investigate the problem of large-scale mobile crowd-tasking, where a large pool of citizen crowd-workers are used to perform a variety of location-specific urban logistics tasks. Current approaches to such mobile crowd-tasking are very decentralized: a crowd-tasking platform usually provides each worker a set of available tasks close to the worker's current location; each worker then independently chooses which tasks she wants to accept and perform. In contrast, we propose TRACCS, a more coordinated task assignment approach, where the crowd-tasking platform assigns a sequence of tasks to each worker, taking into account their expected location trajectory over a wider time …
Sew-Ing A Simple Endorsement Web To Incentivize Trustworthy Participatory Sensing, T. Luo, S. Kanhere, Hwee-Pink Tan
Sew-Ing A Simple Endorsement Web To Incentivize Trustworthy Participatory Sensing, T. Luo, S. Kanhere, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Two crucial issues to the success of participatory sensing are (a) how to incentivize the large crowd of mobile users to participate and (b) how to ensure the sensing data to be trustworthy. While they are traditionally being studied separately in the literature, this paper proposes a Simple Endorsement Web (SEW) to address both issues in a synergistic manner. The key idea is (a) introducing a social concept called nepotism into participatory sensing, by linking mobile users into a social “web of participants” with endorsement relations, and (b) overlaying this network with investment-like economic implications. The social and economic layers …
Stfu Noob!: Predicting Crowdsourced Decisions On Toxic Behavior In Online Games, Jeremy Blackburn, Haewoon Kwak
Stfu Noob!: Predicting Crowdsourced Decisions On Toxic Behavior In Online Games, Jeremy Blackburn, Haewoon Kwak
Research Collection School Of Computing and Information Systems
One problem facing players of competitive games is negative, or toxic, behavior. League of Legends, the largest eSport game, uses a crowdsourcing platform called the Tribunal to judge whether a reported toxic player should be punished or not. The Tribunal is a two stage system requiring reports from those players that directly observe toxic behavior, and human experts that review aggregated reports. While this system has successfully dealt with the vague nature of toxic behavior by majority rules based on many votes, it naturally requires tremendous cost, time, and human efforts. In this paper, we propose a supervised learning approach …
Free Market Of Crowdsourcing: Incentive Mechanism Design For Mobile Sensing, Xinglin Zhang, Zheng Yang, Zimu Zhou, Haibin Cai, Lei Chen, Xiang-Yang Li
Free Market Of Crowdsourcing: Incentive Mechanism Design For Mobile Sensing, Xinglin Zhang, Zheng Yang, Zimu Zhou, Haibin Cai, Lei Chen, Xiang-Yang Li
Research Collection School Of Computing and Information Systems
Off-the-shelf smartphones have boosted large scale participatory sensing applications as they are equipped with various functional sensors, possess powerful computation and communication capabilities, and proliferate at a breathtaking pace. Yet the low participation level of smartphone users due to various resource consumptions, such as time and power, remains a hurdle that prevents the enjoyment brought by sensing applications. Recently, some researchers have done pioneer works in motivating users to contribute their resources by designing incentive mechanisms, which are able to provide certain rewards for participation. However, none of these works considered smartphone users’ nature of opportunistically occurring in the area …
Free Market Of Crowdsourcing: Incentive Mechanism Design For Mobile Sensing, Xinglin Zhang, Zheng Yang, Zimu Zhou, Haibin Cai, Lei Chen, Xiang-Yang Li
Free Market Of Crowdsourcing: Incentive Mechanism Design For Mobile Sensing, Xinglin Zhang, Zheng Yang, Zimu Zhou, Haibin Cai, Lei Chen, Xiang-Yang Li
Research Collection School Of Computing and Information Systems
Off-the-shelf smartphones have boosted large scale participatory sensing applications as they are equipped with various functional sensors, possess powerful computation and communication capabilities, and proliferate at a breathtaking pace. Yet the low participation level of smartphone users due to various resource consumptions, such as time and power, remains a hurdle that prevents the enjoyment brought by sensing applications. Recently, some researchers have done pioneer works in motivating users to contribute their resources by designing incentive mechanisms, which are able to provide certain rewards for participation. However, none of these works considered smartphone users’ nature of opportunistically occurring in the area …