Using High-dimensional Semantic Spaces Derived from Large Text Corpora
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Using High-dimensional Semantic Spaces Derived from Large Text Corpora

Abstract

Attempting to derive models of semantic memory using psychometric techniques has a long history in cognitive psychology dating back at least to Osgood (1957). Many others have used multidimensional scaling on human judgements of similarity (e.g., Shepard, 1962, 1974; Rips, Shoben, & Smith, 1973; Schvaneveldt, 1990). Recently, a small group of investigators have been using large corpora, 1 million to 500 million words, to develop cognitively plausible high-dimensional semantic models without the need for human judgements on stimuli. These models have become increasingly better at explaining a wide range of cognitive pheno

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