We present a FrameNet-based semantic role labeling system for Swedish text. As training data for the system, we used an annotated corpus that we produced by transferring FrameNet ...
Current Semantic Role Labeling technologies are based on inductive algorithms trained over large scale repositories of annotated examples. Frame-based systems currently make use o...
Danilo Croce, Cristina Giannone, Paolo Annesi, Rob...
We introduce a novel active learning algorithm for classification of network data. In this setting, training instances are connected by a set of links to form a network, the label...
This paper presents a text/graphic labelling for ancient printed documents. Our approach is based on the extraction and the quantification of the various orientations that are pre...
Building a shared and widely accessible repository, in order for scientists and end users to exploit it easily, results in tackling a variety of issues. Among others, the need for ...
Floriana Esposito, Stefano Ferilli, Nicola Di Maur...