COMPENDIUM: A text summarization system for generating abstracts of research papers

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10045/33138
Información del item - Informació de l'item - Item information
Título: COMPENDIUM: A text summarization system for generating abstracts of research papers
Autor/es: Lloret, Elena | Romá-Ferri, María Teresa | Palomar, Manuel
Grupo/s de investigación o GITE: Procesamiento del Lenguaje y Sistemas de Información (GPLSI)
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos | Universidad de Alicante. Departamento de Enfermería
Palabras clave: Human language technologies | NLP applications | Text summarization | Information systems
Área/s de conocimiento: Lenguajes y Sistemas Informáticos
Fecha de publicación: 14-ago-2013
Editor: Elsevier
Cita bibliográfica: LLORET, Elena; ROMÁ-FERRI, María Teresa; PALOMAR, Manuel. "COMPENDIUM: A text summarization system for generating abstracts of research papers". Data & Knowledge Engineering. Article In Press (Available online 14 August 2013). ISSN 0169-023X
Resumen: This article analyzes the appropriateness of a text summarization system, COMPENDIUM, for generating abstracts of biomedical papers. Two approaches are suggested: an extractive (COMPENDIUM E), which only selects and extracts the most relevant sentences of the documents, and an abstractive-oriented one (COMPENDIUM E–A), thus facing also the challenge of abstractive summarization. This novel strategy combines extractive information, with some pieces of information of the article that have been previously compressed or fused. Specifically, in this article, we want to study: i) whether COMPENDIUM produces good summaries in the biomedical domain; ii) which summarization approach is more suitable; and iii) the opinion of real users towards automatic summaries. Therefore, two types of evaluation were performed: quantitative and qualitative, for evaluating both the information contained in the summaries, as well as the user satisfaction. Results show that extractive and abstractive-oriented summaries perform similarly as far as the information they contain, so both approaches are able to keep the relevant information of the source documents, but the latter is more appropriate from a human perspective, when a user satisfaction assessment is carried out. This also confirms the suitability of our suggested approach for generating summaries following an abstractive-oriented paradigm.
Patrocinador/es: This research was partially supported by the FPI grant (BES-2007-16268) and the project grants TEXT-MESS (TIN2006-15265-C06-01), TEXT-MESS 2.0 (TIN2009-13391-C04) and LEGOLANG (TIN2012-31224) from the Spanish Government. It has been also funded by the Valencian Government (grant no. PROMETEO/2009/119 and ACOMP/2011/001).
URI: http://hdl.handle.net/10045/33138
ISSN: 0169-023X (Print) | 1872-6933 (Online)
DOI: 10.1016/j.datak.2013.08.005
Idioma: eng
Tipo: info:eu-repo/semantics/article
Revisión científica: si
Versión del editor: http://dx.doi.org/10.1016/j.datak.2013.08.005
Aparece en las colecciones:INV - GPLSI - Artículos de Revistas

Archivos en este ítem:
Archivos en este ítem:
Archivo Descripción TamañoFormato 
Thumbnail1-s2.0-S0169023X13000815-main.pdfVersión final (acceso restringido)1,07 MBAdobe PDFAbrir    Solicitar una copia


Todos los documentos en RUA están protegidos por derechos de autor. Algunos derechos reservados.