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dc.contributor.authorLópez, Vivian
dc.contributor.authorAguila, Ramiro
dc.contributor.authorAlonso, Luis
dc.contributor.authorMoreno García, María Navelonga 
dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.date.accessioned2017-09-05T11:01:36Z
dc.date.available2017-09-05T11:01:36Z
dc.date.issued2012
dc.identifier.citationNeurocomputing. Volumen 75 (1), pp. 88-97. Elsevier BV.
dc.identifier.issn0925-2312 (Print)
dc.identifier.urihttp://hdl.handle.net/10366/134371
dc.description.abstractIn this paper we describe both the theoretical and practical results of a novel approach that combines hybrid techniques of association analysis and classical sequentiation algorithms of genomics to generate the grammatical structures of a specific language. We used an application of a compiler generator system that allows a practical application to be developed within the area of grammarware, where the concepts of language analysis are applied to other disciplines, such as bioinformatics. The tool allows the complexity of the obtained grammar to be measured automatically from textual data. A technique involving the incremental discovery of sequential patterns is presented to obtain simplified production rules, and compacted with bioinformatics criteria to make up a grammar.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherElsevier BV
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleGrammatical inference with bioinformatics criteria
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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