Estimating uncertainty of categorical Web data

Abstract

Web data often manifest high levels of uncertainty. We focus on categorical Web data and we represent these uncertainty levels as first or second order uncertainty. By means of concrete examples, we show how to quantify and handle these uncertainties using the Beta- Binomial and the Dirichlet-Multinomial models, as well as how take into account possibly unseen categories in our samples by using the Dirichlet Process.