Introducing Collaboration in Competitive Crowdsourcing Markets

IEEE Intelligent Systems(2019)

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摘要
Crowdsourcing is a promising way of solving problems in a distributed manner within a stipulated time. The working principle of crowdsourcing platforms can be either competitive or collaborative. In both of this, crowd workers (solvers) get a remuneration either predecided through bidding or preannounced by the requester (task provider). Even being convenient, the curse of competitiveness often reduces the participation of workers. We highlight that by introducing collaboration in competitive crowdsourcing markets, we can handle decomposable-type tasks in an efficient way. Here, we propose a novel mechanism for the said purpose. If the tasks are decomposable, workers may get interest to collaborate on the subtasks. This increases the chance of receiving more number of cost-effective solutions. The proposed mechanism encourages the workers to collaborate by sharing the remuneration thoughtfully. Thus, both the requester and crowd workers get benefit from the system. We demonstrate the effectiveness of the proposed mechanism through empirical analysis.
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关键词
Task analysis,Remuneration,Crowdsourcing,Collaboration,Intelligent systems,Biological system modeling,Matrix decomposition
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