A corpus to support eHealth Knowledge Discovery technologies

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/91553
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dc.contributorProcesamiento del Lenguaje y Sistemas de Información (GPLSI)es_ES
dc.contributor.authorPiad-Morffis, Alejandro-
dc.contributor.authorGutiérrez, Yoan-
dc.contributor.authorMuñoz, Rafael-
dc.contributor.otherUniversidad de Alicante. Departamento de Lenguajes y Sistemas Informáticoses_ES
dc.identifier.citationJournal of Biomedical Informatics. 2019, 94: 103172. doi:10.1016/j.jbi.2019.103172es_ES
dc.identifier.issn1532-0464 (Print)-
dc.identifier.issn1532-0480 (Online)-
dc.description.abstractThis paper presents and describes eHealth-KD corpus. The corpus is a collection of 1173 Spanish health-related sentences manually annotated with a general semantic structure that captures most of the content, without resorting to domain-specific labels. The semantic representation is first defined and illustrated with example sentences from the corpus. Next, the paper summarizes the process of annotation and provides key metrics of the corpus. Finally, three baseline implementations, which are supported by machine learning models, were designed to consider the complexity of learning the corpus semantics. The resulting corpus was used as an evaluation scenario in TASS 2018 (Martínez-Cámara et al., 2018) and the findings obtained by participants are discussed. The eHealth-KD corpus provides the first step in the design of a general-purpose semantic framework that can be used to extract knowledge from a variety of domains.es_ES
dc.description.sponsorshipThis research has been supported by the University of Alicante and University of Havana. Moreover, it has also been partially funded by both aforementioned universities and the Generalitat Valenciana (Conselleria d’Educació, Investigació, Cultura i Esport) through the projects PROMETEO/2018/089, PROMETEU/2018/089; Social-Univ 2.0 (ENCARGO-INTERNOOMNI-1); and PINGVALUE3-18Y.es_ES
dc.rights© 2019 Elsevier Inc.es_ES
dc.subjectKnowledge discoveryes_ES
dc.subject.otherLenguajes y Sistemas Informáticoses_ES
dc.titleA corpus to support eHealth Knowledge Discovery technologieses_ES
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