Kernel Methods for Minimally Supervised WSD
@article{Giuliano2009KernelMF, title={Kernel Methods for Minimally Supervised WSD}, author={Claudio Giuliano and Alfio Massimiliano Gliozzo and Carlo Strapparava}, journal={Computational Linguistics}, year={2009}, volume={35}, pages={513-528} }
We present a semi-supervised technique for word sense disambiguation that exploits external knowledge acquired in an unsupervised manner. In particular, we use a combination of basic kernel functions to independently estimate syntagmatic and domain similarity, building a set of word-expert classifiers that share a common domain model acquired from a large corpus of unlabeled data. The results show that the proposed approach achieves state-of-the-art performance on a wide range of lexical sample… CONTINUE READING
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