Sciweavers

Share
ALDT
2011
Springer

Learning Complex Concepts Using Crowdsourcing: A Bayesian Approach

7 years 10 months ago
Learning Complex Concepts Using Crowdsourcing: A Bayesian Approach
Abstract. We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated according to (noisy) observations from experts, whose behaviors are modeled using discrete types. We propose recommendation techniques, inference methods, and query selection strategies to assist a user charged with choosing a configuration that satisfies some (partially known) concept. Our model is able to simultaneously learn the concept definition and the types of the experts. We evaluate our model with simulations, showing that our Bayesian strategies are effective even in large concept spaces with many uninformative experts.
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton
Added 12 Dec 2011
Updated 12 Dec 2011
Type Journal
Year 2011
Where ALDT
Authors Paolo Viappiani, Sandra Zilles, Howard J. Hamilton, Craig Boutilier
Comments (0)
books