We examine the utility of multiple types of turn-level and contextual linguistic features for automatically predicting student emotions in human-human spoken tutoring dialogues. W...
Abstract. Discovering significant meta-information from document collections is a critical factor for knowledge distribution and preservation. This paper presents a system that im...
Floriana Esposito, Stefano Ferilli, Teresa Maria A...
The authors of topic map-based learning resources face major difficulties in constructing the underlying ontologies. In this paper we propose two approaches to address this problem...
Word meaning ambiguity has always been an important problem in information retrieval and extraction, as well as, text mining (documents clustering and classification). Knowledge di...
Henryk Rybinski, Marzena Kryszkiewicz, Grzegorz Pr...
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. ...