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dc.contributor.authorSerrano Moreno, José Ignacio-
dc.contributor.authorCastillo Sobrino, María Dolores del-
dc.date.accessioned2010-02-26T12:10:30Z-
dc.date.available2010-02-26T12:10:30Z-
dc.date.issued2006-10-
dc.identifier.citationNeural Information Processingen_US
dc.identifier.citationLecture Notes in Computer Science 4232, pp.237-246, 2006en_US
dc.identifier.urihttp://hdl.handle.net/10261/21708-
dc.description.abstractAbstract. Traditional document indexing methods, although useful, do not take into account some important aspects of language, such as syntax and semantics. Unlikely, semantic hyperspaces are mathematical and statistical-based techniques that do it. However, although they are an improvement on traditional methods, the output representation is still vector like. This paper proposes a computational model of text reading, called Cognitive Reading Indexing (CRIM), inspired by some aspects of human reading cognition, such as sequential perception, temporality, memory, forgetting and inferences. The model produces not vectors but nets of activated concepts. This paper is focused on indexing or representing documents that way so that they can be labeled or retrieved, presenting promising results. The system was applied to model human subjects as well, and some interesting results were obtained.en_US
dc.format.extent192757 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsopenAccessen_US
dc.titleText Representation by a Computational Model of Readingen_US
dc.typecapítulo de libroen_US
dc.identifier.doi10.1007/11893028-
dc.description.peerreviewedPeer revieweden_US
dc.relation.publisherversionhttp://www.springerlink.com/content/tvk66403wqk21088/?p=84f7256c2e26425dbc7abbfee9ae67d7&pi=2en_US
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