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» Learning to Merge Word Senses
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BMCBI
2006
151views more  BMCBI 2006»
13 years 4 months ago
Machine learning and word sense disambiguation in the biomedical domain: design and evaluation issues
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...
Hua Xu, Marianthi Markatou, Rositsa Dimova, Hongfa...
FLAIRS
2011
12 years 8 months ago
Impact of Word Sense Disambiguation on Ordering Dictionary Definitions in Vocabulary Learning Tutors
Past research has shown that dictionaries and glosses can be beneficial in computer assisted language learning, particularly in vocabulary learning. We propose that L2 vocabulary ...
Kevin Dela Rosa, Maxine Eskenazi
CORR
2000
Springer
132views Education» more  CORR 2000»
13 years 4 months ago
A Comparison between Supervised Learning Algorithms for Word Sense Disambiguation
This paper describes a set of comparative experiments, including cross{corpus evaluation, between ve alternative algorithms for supervised Word Sense Disambiguation (WSD), namely ...
Gerard Escudero, Lluís Màrquez, Germ...
NLP
2000
13 years 8 months ago
Learning Rules for Large-Vocabulary Word Sense Disambiguation: A Comparison of Various Classifiers
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...