We present two algorithms for supporting semi-automatic ontology building, integrated in WPro, a new architecture for ontology learning from Web documents. The first algorithm auto...
Daniele Bagni, Marco Cappella, Maria Teresa Pazien...
We propose a novel, computationally efficient generative topographic model for inferring low dimensional representations of high dimensional data sets, designed to exploit data s...
We have explored a novel method to find textual relations in electronic documents using genetic programming and semantic networks. This can be used for enhancing information retri...
In this paper, we present a structural learning model for joint sentiment classification and aspect analysis of text at various levels of granularity. Our model aims to identify ...
This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...