T2Know: An Advance Scientific-Tecnical Text Analysis Platform for Trend and Knowledge Extraction Using NLP Techniques

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10045/138196
Información del item - Informació de l'item - Item information
Título: T2Know: An Advance Scientific-Tecnical Text Analysis Platform for Trend and Knowledge Extraction Using NLP Techniques
Autor/es: Muñoz, Rafael | Gutiérrez, Yoan | Montoyo, Andres
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
Palabras clave: Semantics | Semantic document profile | Entity recognition | Language models | Transformers
Fecha de publicación: 23-oct-2023
Editor: CEUR
Cita bibliográfica: SEPLN-PD 2023: Annual Conference of the Spanish Association for Natural Language Processing 2023: Projects and System Demonstrations, Jaén, Spain, September 27-29, 2023. CEUR Workshop Proceedings, Vol-3516
Resumen: The project T2Know presents the use of natural language processing technologies for the creation of a semantic platform of scientific documents via knowledge graphs. This knowledge graph will link relevant parts of each document with those of other documents in such a way that trend analysis and recommendations can be achieved. The goals addressed within the scope of this project include entity recognizers development, profile definition and documents linkage through the use of transformers technologies. As a result, the relevant parts of the documents to be extracted are related not only to the title and affiliation of the authors, but also to article topics such as references, which are also considered relevant parts of the scientific article.
Patrocinador/es: This project is funded by the Valencian Agency for Innovation through the project INNEST/2022/24, partially funded by the Generalitat Valenciana (Conselleria d’Educació, Investigació, Cultura i Esport) through the following projects NL4DISMIS: TLHs for an Equal and Accessible Inclusive Society (CIPROM/2021/021) and T2Know: Platform for advanced analysis of scientific-technical texts to extract trends and knowledge through NLP techniques. (Innest/2022/24). Moreover, it was backed by the work of two COST Actions: CA19134 - “Distributed Knowledge Graphs” and CA19142 - “Leading Platform for European Citizens, Industries, Academia, and Policymakers in Media Accessibility”.
URI: http://hdl.handle.net/10045/138196
ISSN: 1613-0073
Idioma: eng
Tipo: info:eu-repo/semantics/conferenceObject
Derechos: © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Revisión científica: si
Versión del editor: https://ceur-ws.org/Vol-3516/
Aparece en las colecciones:INV - GPLSI - Comunicaciones a Congresos, Conferencias, etc.

Archivos en este ítem:
Archivos en este ítem:
Archivo Descripción TamañoFormato 
ThumbnailMunoz_etal_SEPLN-PD2023.pdf3,56 MBAdobe PDFAbrir Vista previa


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