Word sense disambiguation is typically phrased as the task of labeling a word in context with the best-fitting sense from a sense inventory such as WordNet. While questions have o...
In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characte...
Georgios Paliouras, Vangelis Karkaletsis, Ion Andr...
We propose a Word Sense Disambiguation (WSD) method that accurately classifies ambiguous words to concepts in the Associative Concept Dictionary (ACD) even when the test corpus an...
Kyota Tsutsumida, Jun Okamoto, Shun Ishizaki, Mako...
Recent research works on unsupervised word sense disambiguation report an increase in performance, which reduces their handicap from the respective supervised approaches for the sa...
George Tsatsaronis, Iraklis Varlamis, Kjetil N&osl...
— Word sense disambiguation (WSD), the task of identifying the intended meanings (senses) of words in context, has been a long-standing research objective for natural language pr...