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A Recommendation of Crowdsourcing Workers Based on Multi-community Collaboration

  • Zhifang Liao
  • Xin Xu
  • Peng Lan
  • Jun LongEmail author
  • Yan Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11895)

Abstract

Currently there are problems such as fuzzy workers’ characteristics and complex human relations existing on many crowdsourcing platforms, which lead to the difficulty in the recommendation of workers to complete tasks on crowdsourcing platforms. Aiming at worker recommendations in categorical tasks on crowdsourcing platforms, this paper proposes a recommendation considering workers’ multi-community characteristics. It takes factors such as worker’s reputation, preference and activity into consideration. Finally, based on the characteristics of community intersections, it recommends Top-N workers. The results show the recommendations generated by the algorithm proposed in this paper performs the best comprehensively.

Keywords

Crowdsourcing Recommendation Community discovery 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Zhifang Liao
    • 1
  • Xin Xu
    • 1
  • Peng Lan
    • 1
  • Jun Long
    • 1
    Email author
  • Yan Zhang
    • 2
  1. 1.Department of Software Engineering, School of Computer Science and EngineeringCentral South UniversityChangshaChina
  2. 2.Glasgow Caledonian UniversityGlasgowUK

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