{"pk":32849,"title":"Context-Sensitive, Distributed, Variable-Representation Category Formation","subtitle":null,"abstract":"This paper describes INC2, an incremental category formation system which implements the concepts of family resemblance, contrast-model-based similarity, and context-sensitive, distributed probabilistic representation. The system is evaluated in terms of both the structure of categories/hierarchies it generates and its categorization (prediction) accuracy in both noise-free and noisy domains. Performance is shown to be comparable to both humans and existing leaming-from-example systems, even though the system is not provided with any category membership information during the category formation stage.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Paper Presentations -- Category Formation and Similarity","is_remote":true,"remote_url":"https://escholarship.org/uc/item/7vd887f5","frozenauthors":[{"first_name":"Mirsad","middle_name":"","last_name":"Hadzikadic","name_suffix":"","institution":"University of North Carolina","department":""},{"first_name":"Paul","middle_name":"","last_name":"Elia","name_suffix":"","institution":"University of North Carolina","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1991-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/32849/galley/23909/download/"}]}