{"pk":33030,"title":"Using High-dimensional Semantic Spaces Derived from Large Text Corpora","subtitle":null,"abstract":"Attempting to derive models of semantic memory using \npsychometric techniques has a long history in cognitive \npsychology dating back at least to Osgood (1957). Many others \nhave used multidimensional scaling on human judgements of \nsimilarity (e.g., Shepard, 1962, 1974; Rips, Shoben, & Smith, \n1973; Schvaneveldt, 1990). Recently, a small group of \ninvestigators have been using large corpora, 1 million to 500 \nmillion words, to develop cognitively plausible \nhigh-dimensional semantic models without the need for human \njudgements on stimuli. These models have become increasingly \nbetter at explaining a wide range of cognitive pheno","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"17","is_remote":true,"remote_url":"https://escholarship.org/uc/item/3s1164pd","frozenauthors":[{"first_name":"Curt","middle_name":"","last_name":"Burgess","name_suffix":"","institution":"University of California Riverside","department":""},{"first_name":"Gary","middle_name":"","last_name":"Cottrell","name_suffix":"","institution":"University of California, San Diego","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1995-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/33030/galley/24092/download/"}]}