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Probabilistic multi-word spotting in handwritten text images

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Probabilistic multi-word spotting in handwritten text images

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dc.contributor.author Toselli, Alejandro Héctor es_ES
dc.contributor.author Vidal, Enrique es_ES
dc.contributor.author Puigcerver, Joan es_ES
dc.contributor.author Noya-García, Ernesto es_ES
dc.date.accessioned 2020-01-09T21:00:51Z
dc.date.available 2020-01-09T21:00:51Z
dc.date.issued 2019-05-02 es_ES
dc.identifier.issn 1433-7541 es_ES
dc.identifier.uri http://hdl.handle.net/10251/134140
dc.description.abstract [EN] Keyword spotting techniques are becoming cost-effective solutions for information retrieval in handwritten documents. We explore the extension of the single-word, line-level probabilistic indexing approach described in our previous works to allow for page-level search of queries consisting in Boolean combinations of several single-keywords. We propose heuristic rules to combine the single-word relevance probabilities into probabilistically consistent confidence scores of the multi-word boolean combinations. An empirical study, also presented in this paper, evaluates the search performance of word-pair queries involving AND and OR Boolean operations. Results of this study support the proposed approach and clearly show its effectiveness. Finally, a web-based demonstration system based on the proposed methods is presented. es_ES
dc.description.sponsorship This work was partially supported by the Generalitat Valenciana under the Prometeo/2009/014 Project Grant ALMAMATER, Spanish MEC under Grant FPU13/06281, and through the EU projects: HIMANIS (JPICH programme, Spanish grant Ref. PCIN-2015-068) and READ (Horizon-2020 programme, Grant Ref. 674943). es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Pattern Analysis and Applications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Handwritten text processing es_ES
dc.subject Keyword spotting es_ES
dc.subject Multi-word Boolean queries es_ES
dc.subject Image processing es_ES
dc.subject Pattern recognition es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Probabilistic multi-word spotting in handwritten text images es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10044-018-0742-z es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//PCIN-2015-068/ES/INDEXACION DE MANUSCRITOS HISTORICOS PARA BUSQUEDAS CONTROLADAS POR EL USUARIO/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/674943/EU/Recognition and Enrichment of Archival Documents/
dc.relation.projectID info:eu-repo/grantAgreement/Generalitat Valenciana//PROMETEO09%2F2009%2F014/ES/Adaptive learning and multimodality in pattern recognition (Almapater)/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//FPU13%2F06281/ES/FPU13%2F06281/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat 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 Toselli, AH.; Vidal, E.; Puigcerver, J.; Noya-García, E. (2019). Probabilistic multi-word spotting in handwritten text images. Pattern Analysis and Applications. 22(1):23-32. https://doi.org/10.1007/s10044-018-0742-z es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s10044-018-0742-z es_ES
dc.description.upvformatpinicio 23 es_ES
dc.description.upvformatpfin 32 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 22 es_ES
dc.description.issue 1 es_ES
dc.relation.pasarela S\372706 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Ministerio de Educación es_ES
dc.contributor.funder Ministerio de Economía y Empresa es_ES
dc.contributor.funder European Commission es_ES
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