In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...
The paper proposes an integrated framework which uses knowledge representation theory and languages to annotate relevant product information in a semantically rich and unambiguous ...
Michele Ruta, Floriano Scioscia, Eugenio Di Sciasc...
We present a novel reasoning procedure for Horn SHIQ ontologies--SHIQ ontologies that can be translated to the Horn fragment of first-order logic. In contrast to traditional reaso...
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Mitchell et al. (2008) demonstrated that corpus-extracted models of semantic knowledge can predict neural activation patterns recorded using fMRI. This could be a very powerful te...