Generally, ontology learning and population is applied as a semi-automatic approach to knowledge acquisition in natural language understanding systems. That means, after the ontol...
Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely ...
An open issue in data-driven dependency parsing is how to handle non-projective dependencies, which seem to be required by linguistically adequate representations, but which pose ...
We present a method for utilizing unannotated sentences to improve a semantic parser which maps natural language (NL) sentences into their formal meaning representations (MRs). Gi...
Ontology evolution is a complex problem. In our work, we focus on issues related to change management, particularly consistency maintenance and we present in this paper, an overvie...