MS Project Report
With the significant advance of internet and connectivity, crowdsourcing gained more popularity and various crowdsourcing platforms emerged. This project focuses on knowledge-intensive crowdsourcing, in which agents are presented with the tasks that require certain knowledge in domain. Knowledge-intensive crowdsourcing requires agents to have experiences on the specific domain. With the constraint of resources and its trait as sourcing from crowd, platform is likely to draw agents with different levels of expertise and knowledge and asking same task can result in bad performance. Some agents can give better information when they are asked with more general question or more knowledge-specific task or even other task in the same domain. With this intuition of hierarchy, this project depicts knowledge-structure in domain as tree structure and aims to propose methods on how to assign tasks to the agents to realize the ground truth of the data they are presented.
Kim, Dohoon, "Elicitation and aggregation of data in knowledge intensive crowdsourcing" Report Number: (2020). All Computer Science and Engineering Research.