loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

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

Keyword(s): Recommendation Systems, Smart Campus, Collaborative Filtering, Content-Based Filtering.

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 educati onal resources to users. The prototype of the architecture was evaluated using real item data and shown a significant accuracy in the recommendation process. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.97.14.83

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Maruyama, M. ; Silveira, L. ; M. de Oliveira, J. ; Gasparini, I. and Maran, V. (2023). Hybrid Recommender System for Educational Resources to the Smart University Campus Domain. In Proceedings of the 15th International Conference on Computer Supported Education - Volume 1: CSEDU; ISBN 978-989-758-641-5; ISSN 2184-5026, SciTePress, pages 47-56. DOI: 10.5220/0011841900003470

@conference{csedu23,
author={Martin Maruyama and Luan Silveira and José {M. de Oliveira} and Isabela Gasparini and Vinícius Maran},
title={Hybrid Recommender System for Educational Resources to the Smart University Campus Domain},
booktitle={Proceedings of the 15th International Conference on Computer Supported Education - Volume 1: CSEDU},
year={2023},
pages={47-56},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011841900003470},
isbn={978-989-758-641-5},
issn={2184-5026},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Computer Supported Education - Volume 1: CSEDU
TI - Hybrid Recommender System for Educational Resources to the Smart University Campus Domain
SN - 978-989-758-641-5
IS - 2184-5026
AU - Maruyama, M.
AU - Silveira, L.
AU - M. de Oliveira, J.
AU - Gasparini, I.
AU - Maran, V.
PY - 2023
SP - 47
EP - 56
DO - 10.5220/0011841900003470
PB - SciTePress