Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
385861 | Expert Systems with Applications | 2011 | 11 Pages |
In this article, we concentrate in conceptual relations as a source of information for Word Sense Disambiguation (WSD) systems. We start with a review the most relevant research in the field, then we implement our own algorithm. As a starting point we have chosen the conceptual density algorithm of Agirre and Rigau. We generalize the original algorithm, parameterizing many aspects. This new algorithm obtains a relative improvement of 24% in terms of precision and recall. We also offer comparative evaluation of our system with respect to the participants in the SENSEVAL-2 disambiguation competition.We conclude that conceptual relations provide a source of information that is insufficient by itself to achieve good disambiguation results, but can, however, be a very accurate heuristic in a combined system.
Research highlights► Conceptual relations can be exploited for word sense disambiguation purposes. ► Previous conceptual density disambiguation algorithms are expanded. ► Interesting parameter values that improve the original algorithm are discovered. ► Results are compared with the SENSEVAL-2 disambiguation competition participants.