Abstract: In this paper, we present a novel context-dependent approach to modelling word meaning, and apply it to the modelling of metaphor. In distributional semantic approaches, words are represented as points in a high dimensional space generated from co-occurrence statistics; the distances between points may then be used to quantifying semantic relationships. Contrary to other approaches which use static, global representations, our approach discovers contextualised representations by dynamically projecting low-dimensional subspaces; in these \textit...
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Topics: 
Natural language processing
Artificial intelligence