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Laboratory of Ubiquitous, Mobile and Applied Computing (LUMAC), Polytechnic School, Federal University of Santa Maria, Av. Roraima, 1000, Santa Maria, Brazil

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1 Papers

Hybrid Recommender System for Educational Resources to the Smart University Campus Domain

Topics: e-Learning Platforms, Portals; Tools for Educational Communication and Collaboration

Authors: Martin Maruyama ¹ , Luan Silveira ¹ , José M. de Oliveira ² , Isabela Gasparini ³ and Vinícius Maran ¹

Affiliations: ¹ Laboratory of Ubiquitous, Mobile and Applied Computing (LUMAC), Polytechnic School, Federal University of Santa Maria, Av. Roraima, 1000, Santa Maria, Brazil , ² Informatics Institute, Federal University of Rio Grande do Sul, Porto Alegre, Brazil , ³ Universidade do Estado de Santa Catarina (UDESC), Joinville, Brazil

Digital Object Identifier: 10.5220/0011841900003470

Proceedings of CSEDU 2023, ISBN: 978-989-758-641-5

Quick Abstract

The development of new cutting-edge technologies in recent years and the ease of access to the internet, the amount of data circulating on the network have been severely increasing, making it difficult to access quality information and causing many users to waste their time looking for and filtering through data. Thus, recommendation systems appears. They are responsible for searching relevant information to the user through mechanisms capable of recognizing the user’s possible interests and, with the use of recommendation algorithms, bringing the user resources that meet their interests. Actually, recommender systems are applied in many domains, including news, healthcare, and finance. Recently, recommender systems have been applied in smart campus domain, which defines systems and techonologies to be applied in university campus. From this scenario, the objective of this study is to develop a hybrid recommender system, attached to a software architecture, to provide general educational resources to users. The prototype of the architecture was evaluated using real item data and shown a significant accuracy in the recommendation process.