Integrating Gaussian Processes with Word-Sequence Kernels for Bayesian Text Categorization

ID
TR-2006-15
Authors
Maryam Mahdaviani, Sara Forghanizadeh and Giuseppe Carenini
Publishing date
August 12, 2006
Length
8 pages
Abstract
We address the problem of multi-labelled text classification using word-sequence kernels. However, rather than applying them with Support Vector Machine as in previous work, we chose a classifier based on Gaussian Processes. This is a probabilistic non-parametric method that retains a sound probabilistic semantics while overcoming the limitations of parametric methods. We present the empirical evaluation of our approach on the standard Reuters-21578 datasets.