Content-Based Learning Object Recommendation System Using a User Profile Ontology for High School Students

Bruna Morillo-Palacios, Juan Gutiérrez-Cárdenas

Resultado de la investigación: Capítulo del libro/informe/acta de congresoArticulo (Contribución a conferencia)revisión exhaustiva

Resumen

The lack of quality of education in Peruvian schools has caused young people to look for other ways to obtain information, of which the web stands out. However, this tool is made up of billions of web pages, which affects the time each student takes to search. To address this situation, we propose the development of a content-based recommendation system that uses ontologies for data storage. Our recommender system allows the user profile data to be integrated into the model to consider its characteristics as part of the recommendation. We carried out two sets of validations for the evaluation of our proposal, one with expert judgment and the other by gathering the opinion of the end-users. As a result of the first evaluation, we found that 76.25% of the items were highly related to the search. For the second evaluation, we found that our system obtained a usability of 78.67%, considering the opinion of the students tested.

Idioma originalInglés
Título de la publicación alojadaProceedings of the Future Technologies Conference, FTC 2020, Volume 1
EditoresKohei Arai, Supriya Kapoor, Rahul Bhatia
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas838-858
Número de páginas21
ISBN (versión impresa)9783030631277
DOI
EstadoPublicada - 2021
EventoFuture Technologies Conference, FTC 2020 - San Francisco, Estados Unidos
Duración: 5 nov 20206 nov 2020

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen1288
ISSN (versión impresa)2194-5357
ISSN (versión digital)2194-5365

Conferencia

ConferenciaFuture Technologies Conference, FTC 2020
País/TerritorioEstados Unidos
CiudadSan Francisco
Período5/11/206/11/20

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