Reusable Meta-Models for Crowdsourcing Driven Elastic Systems (Invited Paper)
Julian Jarrett, M. Brian Blake · 2016
Elastic systems utilize both human and machine working units to accomplish tasks that are eligible for crowdsourcing. The quality in the results of work completed by either type of computing unit is tantamount on the characteristics they bear. In this paper we draw parallels from our previous work into looking at the suitability of working units in completing viable tasks in crowdsourcing. We seek to understand characteristics for modeling tasks and workers within these types of systems. Based on our experiments and lessons learned in related literature, we propose a dynamic worker-task information meta-model with a corresponding operational workflow model that can be used in a variety of problem domains involving crowdsourced tasks to provide support in making this decision.