This paper presents a method to combine a set of unsupervised algorithms that can accurately disambiguate word senses in a large, completely untagged corpus. Although most of the ...
This paper presents the results of a graph-based method for performing knowledge-based Word Sense Disambiguation (WSD). The technique exploits the structural properties of the gra...
NLPsystem developers and corpus lexicographers would both bene t from a tool for nding and organizing the distinctive patterns of use of words in texts. Such a tool would be an ass...
Background: Word sense disambiguation (WSD) is critical in the biomedical domain for improving the precision of natural language processing (NLP), text mining, and information ret...
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...