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2011
- handle: 10670/1.e0clfj
- hal: hal-00666475
info:eu-repo/semantics/OpenAccess
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Tim van de Cruys et al., « Latent Vector Weighting for Word Meaning in Context », HAL-SHS : linguistique, ID : 10670/1.e0clfj
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This paper presents a novel method for the computation of word meaning in context. We make use of a factorization model in which words, together with their window-based context words and their dependency relations, are linked to latent dimensions. The factorization model allows us to determine which dimensions are important for a particular context, and adapt the dependency-based feature vector of the word accordingly. The evaluation on a lexical substitution task - carried out for both English and French - indicates that our approach is able to reach better results than state-of-the-art methods in lexical substitution, while at the same time providing more accurate meaning representations.