Last month Ph.D. Candidate Jie Yang defended his Ph.D. research with his thesis ‘Crowd Knowledge Creation Acceleration’. He was supervised by Geert-Jan Houben (Web Information Systems).
Jie: "Crowd knowledge creation has shown to be effective for knowledge generation at scale. It plays a central role in both on-line knowledge crowdsourcing systems (like Wikipedia and StackOverflow) and human computation systems (like Amazon MTurk and CrowdFlower).
However, the theory and practice of crowd knowledge creation currently lacks a clear understanding on how to control the process for efficiently generating high-quality knowledge.
My work has therefore been focused on better understanding crowd knowledge creation processes and developing novel methods and tools to accelerate the processes. My thesis shows that by optimally designing three different yet closely connected components of crowd knowledge creation systems, i.e., crowd modelling, task modelling, and task assignment, it is possible to accelerate crowd knowledge creation in a principled and effective way.”
