A corpus to support eHealth Knowledge Discovery technologies
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http://hdl.handle.net/10045/91553
Title: | A corpus to support eHealth Knowledge Discovery technologies |
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Authors: | Piad-Morffis, Alejandro | Gutiérrez, Yoan | Muñoz, Rafael |
Research Group/s: | Procesamiento del Lenguaje y Sistemas de Información (GPLSI) |
Center, Department or Service: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos |
Keywords: | Corpus | Subject-Verb-Object | Knowledge discovery | Spanish | eHealth |
Knowledge Area: | Lenguajes y Sistemas Informáticos |
Issue Date: | Jun-2019 |
Publisher: | Elsevier |
Citation: | Journal of Biomedical Informatics. 2019, 94: 103172. doi:10.1016/j.jbi.2019.103172 |
Abstract: | This 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. |
Sponsor: | This 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. |
URI: | http://hdl.handle.net/10045/91553 |
ISSN: | 1532-0464 (Print) | 1532-0480 (Online) |
DOI: | 10.1016/j.jbi.2019.103172 |
Language: | eng |
Type: | info:eu-repo/semantics/article |
Rights: | © 2019 Elsevier Inc. |
Peer Review: | si |
Publisher version: | https://doi.org/10.1016/j.jbi.2019.103172 |
Appears in Collections: | INV - GPLSI - Artículos de Revistas |
Files in This Item:
File | Description | Size | Format | |
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![]() | Versión final (acceso restringido) | 1,04 MB | Adobe PDF | Open Request a copy |
![]() | Accepted Manuscript (acceso abierto) | 1,15 MB | Adobe PDF | Open Preview |
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