Application of educational resource recommendation techniques on a university campus

The development of the Internet over the years has brought with it a massive increase in the amount of data present on the network, making the search for specific items a slow and complex task. Thus, tools have emerged with the goal of filtering information within websites and platforms, leaving asi...

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Bibliographic Details
Authors: Maran, Vinícius, Maruyama, Martin Hideki Mensch, Silveira, Luan Willig
Format: article
Status:Published version
Publication Date:2023
Country:Brasil
Institution:Universidade Federal de Santa Maria (UFSM)
Repository:Revista Ciência e Natura (Online)
Language:Portuguese
OAI Identifier:oai:ojs.pkp.sfu.ca:article/75195
Online Access:https://periodicos.ufsm.br/cienciaenatura/article/view/75195
Access Level:Open access
Keyword:Recommendation Systems
Smart Campus
Collaborative Filtering
Content-based Filtering
Hybrid System
Sistema de Recomendação
Campus Inteligente
Filtragem Colaborativa
Filtragem baseada em Conteúdo
Sistema Híbrido
Description
Summary:The development of the Internet over the years has brought with it a massive increase in the amount of data present on the network, making the search for specific items a slow and complex task. Thus, tools have emerged with the goal of filtering information within websites and platforms, leaving aside everything that is irrelevant and providing the user with only what is likely to interest them. These tools are called recommendation systems. In addition, the field of education has also been affected by the problem of data overload, especially in recent years with the popularization of online education, where students demand new methods of research and learning beyond the classroom. Therefore, the objective of this article is to develop a personalized recommendation system for educational resources that, based on users' interests, makes predictions and generates lists of items that match their interests. It is also hoped that this platform can help in the integration and development of intelligent university campuses.