UBC-ALM: Combining k-NN with SVD for WSD
نویسندگان
چکیده
This work describes the University of the Basque Country system (UBC-ALM) for lexical sample and all-words WSD subtasks of SemEval-2007 task 17, where it performed in the second and fifth positions respectively. The system is based on a combination of k-Nearest Neighbor classifiers, with each classifier learning from a distinct set of features: local features (syntactic, collocations features), topical features (bag-ofwords, domain information) and latent features learned from a reduced space using Singular Value Decomposition.
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