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PNEPs, NEPs for context free parsing: Application to natural language processing

dc.contributor.authorOrtega de la Puente, Alfonso 
dc.contributor.authorRosal García, Emilio del
dc.contributor.authorPérez Marín, Diana
dc.contributor.authorMercaş, Robert
dc.contributor.authorPerekrestenko, Alexander
dc.contributor.authorAlfonseca, Manuel
dc.contributor.otherUAM. Departamento de Ingeniería Informáticaes_ES
dc.date.accessioned2015-02-26T14:09:49Z
dc.date.available2015-02-26T14:09:49Z
dc.date.issued2009
dc.identifier.citationBio-Inspired Systems: Computational and Ambient Intelligence: 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain, June 10-12, 2009. Proceedings, Part I. Lecture Notes in Computer Science, Volumen 5517. Springer, 2009. 472-479en_US
dc.identifier.isbn978-3-642-02477-1 (print)en_US
dc.identifier.isbn978-3-642-02478-8 (online)en_US
dc.identifier.issn0302-9743 (print)en_US
dc.identifier.issn1611-3349 (online)en_US
dc.identifier.urihttp://hdl.handle.net/10486/664094
dc.descriptionThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02478-8_59en_US
dc.descriptionProceedings of 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain.en_US
dc.description.abstractThis work tests the suitability of NEPs to parse languages. We propose PNEP, a simple extension to NEP, and a procedure to translate a grammar into a PNEP that recognizes the same language. These parsers based on NEPs do not impose any additional constrain to the structure of the grammar, which can contain all kinds of recursive, lambda or ambiguous rules. This flexibility makes this procedure specially suited for Natural Languge Processing (NLP). In a first proof with a simplified English grammar, we got a performance (a linear time complexity) similar to that of the most popular syntactic parsers in the NLP area (Early and its derivatives). All the possible derivations for ambiguous grammars were generateden_US
dc.description.sponsorshipThis work was partially supported by MEC, project TIN2008-02081/TIN and by DGUI CAM/UAM, project CCG08-UAM/TIC-4425.en_US
dc.format.extent9 pág.es_ES
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherSpringer Berlin Heidelbergen_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.rights© Springer-Verlag Berlin Heidelberg 2009en_US
dc.subject.otherComputational Biologyen_US
dc.subject.otherBioinformaticsen_US
dc.subject.otherPattern Recognitionen_US
dc.subject.otherArtificial Intelligenceen_US
dc.subject.otherData Miningen_US
dc.subject.otherKnowledge Discoveryen_US
dc.titlePNEPs, NEPs for context free parsing: Application to natural language processingen_US
dc.typeconferenceObjecten
dc.typebookParten_US
dc.subject.ecienciaInformáticaes_ES
dc.relation.publisherversionhttp://dx.doi.org/978-3-642-02478-8
dc.identifier.doi10.1007/978-3-642-02478-8_59
dc.identifier.publicationfirstpage472
dc.identifier.publicationlastpage479
dc.identifier.publicationvolume5517
dc.relation.eventdateJune 10-12, 2009en_US
dc.relation.eventnumber10
dc.relation.eventplaceSalamanca (Spain)en_US
dc.relation.eventtitle10th International Work-Conference on Artificial Neural Networks, IWANN 2009en_US
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dc.contributor.groupHerramientas Interactivas Avanzadas (ING EPS-003)es_ES
dc.rights.accessRightsopenAccessen
dc.authorUAMAlfonseca Moreno, Manuel (258923)
dc.authorUAMPérez Marín, Diana Rosario (260499)
dc.facultadUAMEscuela Politécnica Superior


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