This paper explores the use of two graph algorithms for unsupervised induction and tagging of nominal word senses based on corpora. Our main contribution is the optimization of th...
This paper describes a method for learner modelling for use within simulation-based learning environments. The goal of the learner modelling system is to provide the learner with a...
We present a novel hybrid approach for Word Sense Disambiguation (WSD) which makes use of a relational formalism to represent instances and background knowledge. It is built using...
Word Sense Disambiguation (WSD), in the field of Natural Language Processing (NLP), consists in assigning the correct sense (semantics) to a word form (lexeme) by means of the cont...
Davide Buscaldi, Giovanna Guerrini, Marco Mesiti, ...
Resolving polysemy and synonymy is required for high-quality information extraction. We present ConceptResolver, a component for the Never-Ending Language Learner (NELL) (Carlson ...