Architecture for Efficient String Dictionaries in E-Learning
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Título: | Architecture for Efficient String Dictionaries in E-Learning |
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Autor/es: | Ferrández, Antonio | Peral, Jesús | Mora, Higinio | Gil, David |
Grupo/s de investigación o GITE: | Procesamiento del Lenguaje y Sistemas de Información (GPLSI) | Lucentia | Informática Industrial y Redes de Computadores |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos | Universidad de Alicante. Departamento de Tecnología Informática y Computación |
Palabras clave: | String dictionaries | E-learning architecture | Context awareness in learning process |
Área/s de conocimiento: | Lenguajes y Sistemas Informáticos | Arquitectura y Tecnología de Computadores |
Fecha de publicación: | 18-oct-2018 |
Editor: | MDPI |
Cita bibliográfica: | Ferrández A, Peral J, Mora H, Gil D. Architecture for Efficient String Dictionaries in E-Learning. Proceedings. 2018; 2(19):1251. doi:10.3390/proceedings2191251 |
Resumen: | E-Learning is a response to the new educational needs of society and an important development in Information and Communication Technologies. However, this trend presents many challenges, such as the lack of an architecture that allows a unified management of heterogeneous string dictionaries required by all the users of e-learning environments, which we face in this paper. We mean the string dictionaries needed in information retrieval, content development, “key performance indicators” generation and course management applications. As an example, our approach can deal with different indexation dictionaries required by the course contents and the different online forums that generate a huge number of messages with an unordered structure and a great variety of topics. Our architecture will generate an only dictionary that is shared by all the stakeholders involved in the e-learning process. |
Patrocinador/es: | This work was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) under Project SEQUOIA-UA (TIN2015-63502-C3-3-R), Project RESCATA (TIN2015-65100-R) and Project PROMETEO/2018/089; and in part by the Spanish Research Agency (AEI) and the European Regional Development Fund (FEDER) under Project CloudDriver4Industry (TIN2017-89266-R). |
URI: | http://hdl.handle.net/10045/82429 |
ISSN: | 2504-3900 |
DOI: | 10.3390/proceedings2191251 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.3390/proceedings2191251 |
Aparece en las colecciones: | INV - LUCENTIA - Artículos de Revistas INV - I2RC - Artículos de Revistas INV - GPLSI - Artículos de Revistas INV - AIA - Artículos de Revistas |
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