Computer Science – Computation and Language
Scientific paper
2001-07-03
Computer Science
Computation and Language
12 pages, 3 figures, published in the proceedings of NLDB'01
Scientific paper
We explore many ways of using conceptual distance measures in Word Sense Disambiguation, starting with the Agirre-Rigau conceptual density measure. We use a generalized form of this measure, introducing many (parameterized) refinements and performing an exhaustive evaluation of all meaningful combinations. We finally obtain a 42% improvement over the original algorithm, and show that measures of conceptual distance are not worse indicators for sense disambiguation than measures based on word-coocurrence (exemplified by the Lesk algorithm). Our results, however, reinforce the idea that only a combination of different sources of knowledge might eventually lead to accurate word sense disambiguation.
Fernandez-Amoros David
Gonzalo Julio
Verdejo Felisa
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