Word Sense Disambiguation with THESSOM

Word sense disambiguation automatically determines the appropriate senses of a word in context. We have previously shown that self-organized document maps have properties similar to a large-scale semantic
structure that is useful for word sense disambiguation.
In this article we formalize THESSOM, which is an algorithm for word sense disambiguation using self-organized document maps created with WEBSOM. The algorithm is tested on the SENSEVAL-2 bench-mark data and shown to be on a par with the top three contenders of the SENSEVAL-2 competition.
We also show that the performance of the algorithm improves when using more advanced linguistic features for creating the WEBSOM maps.