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On the optimal decision rule for sequential interactive structured prediction

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On the optimal decision rule for sequential interactive structured prediction

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dc.contributor.author Alabau, Vicent es_ES
dc.contributor.author Sanchis Navarro, José Alberto es_ES
dc.contributor.author Casacuberta Nolla, Francisco es_ES
dc.date.accessioned 2014-09-26T17:21:31Z
dc.date.available 2014-09-26T17:21:31Z
dc.date.issued 2012-12
dc.identifier.issn 0167-8655
dc.identifier.uri http://hdl.handle.net/10251/40331
dc.description This is the author’s version of a work that was accepted for publication in Pattern Recognition Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern Recognition Letters [Volume 33, Issue 16, 1 December 2012, Pages 2226–2231] DOI: 10.1016/j.patrec.2012.07.010 es_ES
dc.description.abstract [EN] Interactive structured prediction (ISP) is an emerging framework for structured prediction (SP) where the user and the system collaborate to produce a high quality output. Typically, search algorithms applied to ISP problems have been based on the algorithms for fully-automatic SP systems. However, the decision rule applied should not be considered as optimal since the goal in ISP is to reduce human effort instead of output errors. In this work, we present some insight into the theory of the sequential ISP search problem. First, it is formulated as a decision theory problem from which a general analytical formulation of the opti- mal decision rule is derived. Then, it is compared with the standard formulation to establish under what conditions the standard algorithm should perform similarly to the optimal decision rule. Finally, a general and practical implementation is given and evaluated against three classical ISP problems: interactive machine translation, interactive handwritten text recognition, and interactive speech recognition. es_ES
dc.description.sponsorship The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under Grant agreement no. 287576 (CasMaCat), and from the Spanish MEC/MICINN under the MIPRCV "Consolider Ingenio 2010" program (CSD2007-00018) and iTrans2 (TIN2009-14511) project. It is also supported by the Generalitat Valenciana under grant ALMPR (Prometeo/2009/01) and GV/2010/067. The authors thank the anonymous reviewers for their criticisms and suggestions. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation info:eu-repo/grantAgreement/GVA//GV%2F2010%2F067/ es_ES
dc.relation info:eu-repo/grantAgreement/GVA//PROMETEO09%2F2009%2F014/ES/Adaptive learning and multimodality in pattern recognition (Almapater)/
dc.relation.ispartof Pattern Recognition Letters es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Interactive pattern recognition es_ES
dc.subject Minimum Bayes risk es_ES
dc.subject Machine translation es_ES
dc.subject Handwritten text recognition es_ES
dc.subject Automatic speech recognition es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title On the optimal decision rule for sequential interactive structured prediction es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.patrec.2012.07.010
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/287576/EU/Cognitive Analysis and Statistical Methods for Advanced Computer Aided Translation/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MEC//CSD2007-00018/ES/Multimodal Intraction in Pattern Recognition and Computer Visionm/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2009-14511/ES/Traduccion De Textos Y Transcripcion De Voz Interactivas/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Alabau, V.; Sanchis Navarro, JA.; Casacuberta Nolla, F. (2012). On the optimal decision rule for sequential interactive structured prediction. Pattern Recognition Letters. 33(16):2226-2231. https://doi.org/10.1016/j.patrec.2012.07.010 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.patrec.2012.07.010 es_ES
dc.description.upvformatpinicio 2226 es_ES
dc.description.upvformatpfin 2231 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 33 es_ES
dc.description.issue 16 es_ES
dc.relation.senia 234048
dc.contributor.funder European Commission
dc.contributor.funder Ministerio de Ciencia e Innovación
dc.contributor.funder Generalitat Valenciana
dc.contributor.funder Ministerio de Educación y Ciencia es_ES


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