Interoperability and Scalability for Worker-Job Matching across Crowdsourcing Platforms
Julian Jarrett, M. Brian Blake · 2017
Crowdsourcing labor market platforms consist of a variety of jobs spanning multiple problem domains and their respective specialized or diverse worker pools. Each platform currently operates independently and isolated from the potential benefits of sharing job and worker pool data across platforms. Previous work introduces infrastructure that optimizes the sharing of both job and worker data collectively, called the open push-pull model. In this paper, to support automated recommendation of workers, we introduce an interoperability standard and computational method that facilitates the aggregation of job data while supporting scalability in response to increasing volumes of data. (i.e. workers and jobs continuously entering the system).