Knowledge representation for basic visual categories

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2344

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DC Field	Value	Language
dc.contributor.author	Phelps, R I	-
dc.contributor.author	Musgrove, P B	-
dc.coverage.spatial	18	en
dc.date.accessioned	2008-06-03T15:16:35Z	-
dc.date.available	2008-06-03T15:16:35Z	-
dc.date.issued	1985	-
dc.identifier.citation	Maths Technical Papers (Brunel University). January 1985, pp 1-18	en
dc.identifier.uri	http://bura.brunel.ac.uk/handle/2438/2344	-
dc.description.abstract	This paper reports work on a model of machine learning which is based on the psychological theory of prototypical concepts. This theory is that concepts learnt naturally from interaction with the environment (basic categories) are not structured or defined in logical terms but are clustered in accordance with their similarity to a central prototype, representing the "most typical'' member.	en
dc.format.extent	107138 bytes	-
dc.format.mimetype	application/pdf	-
dc.language.iso	en	-
dc.publisher	Brunel University	en
dc.relation.ispartof	Brunel University Mathematics Technical Papers collection;	-
dc.relation.ispartofseries	;TR/03/85	-
dc.subject	learning	en
dc.subject	categorization	en
dc.subject	prototypes	en
dc.subject	knowledge representation	en
dc.title	Knowledge representation for basic visual categories	en
dc.type	Research Paper	en
Appears in Collections:	Dept of Mathematics Research Papers Mathematical Sciences

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