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

Bruna Morillo-Palacios, Juan Gutiérrez-Cárdenas

Research output: Chapter in Book/Report/Conference proceedingChapter


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.

Original languageEnglish
Title of host publicationAdvances in Intelligent Systems and Computing
EditorsKohei Arai, Supriya Kapoor, Rahul Bhatia
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages21
ISBN (Print)9783030631277
StatePublished - 31 Oct 2020
EventFuture Technologies Conference, FTC 2020 - San Francisco, United States
Duration: 5 Nov 20206 Nov 2020

Publication series

NameAdvances in Intelligent Systems and Computing


ConferenceFuture Technologies Conference, FTC 2020
Country/TerritoryUnited States
CitySan Francisco


  • Content based
  • Education
  • Learning objects
  • Ontologies
  • Recommender system


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