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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