GP-selector: a generic participant selection framework for mobile crowdsourcing systems

Abstract

Participant selection is a common and crucial function for mobile crowdsourcing (MCS) systems or platforms. This paper introduces a generic framework, named GP-Selector, to handle the participant selection from MCS task creation time to runtime. Compared to existing approaches, ours has the following two unique features. 1) In the task creation time, it assists task creators with diverse levels of programming skills to define basic requirements of participant selection. 2) In the runtime, it adopts a two-phase selection process to select participants who not only meet the basic requirements but also are willing to accept the task. Specifically, we utilize the state-of-the-art techniques including ontology modeling, end-user programming and multi-classifier fusion to implement GP-Selector. We evaluate GP-Selector extensively in three aspects: the end-user task creation, the expressiveness of the core ontology model, and the willingness-based selection algorithm. The evaluation results demonstrate the usability and effectiveness.

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Acknowledgments

This work is supported by the Key Program of National Natural Science Foundation of China (91546203) and Chinese Postdoctoral Science Foundation (2016M600014).

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Correspondence to Jiangtao Wang or Yasha Wang.

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This article belongs to the Topical Collection: Special Issue on Mobile Crowdsourcing

Guest Editors: Bin Guo, Xing Xie, Raghu K. Ganti, Daqing Zhang, and Zhu Wang

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Wang, J., Wang, Y., Wang, L. et al. GP-selector: a generic participant selection framework for mobile crowdsourcing systems. World Wide Web 21, 759–782 (2018). https://doi.org/10.1007/s11280-017-0480-y

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Keywords

  • Mobile crowdsourcing
  • Mobile crowdsensing
  • Participant selection