Recommender system for learning objects based in the fusion of social signals, interests, and preferences of learner users in ubiquitous e-learning systems

Author:

da S. Dias AlessandroORCID,Wives Leandro K.

Funder

Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior

Publisher

Springer Science and Business Media LLC

Subject

Management Science and Operations Research,Computer Science Applications,Hardware and Architecture

Reference41 articles.

1. Adomavicius G, Tuzhilin A (2015) Context-aware recommender systems. In: Ricci F, Rokach L, Shapira B (eds) Recommender systems handbook. Springer, Boston

2. Alexander A, Kernohan W, Mccullagh P (2004) Self directed and lifelong learning. Global Health Informatics Education - Stud Health Technol Inform 109:152–166

3. Amatriain X, Pujol JM (2015) Data mining methods for recommender systems. In: Ricci F, Rokach L, Shapira B (eds) Recommender systems handbook. Springer, Boston

4. Bell RM, Koren Y (2007) Scalable collaborative filtering with jointly derived neighborhood interpolation weights. Proceedings of the 2007 Seventh IEEE International Conference on Data Mining (ICDM '07). IEEE Computer Society, Washington, DC, pp 43–52. https://doi.org/10.1109/ICDM.2007.90

5. Bhargava P, Phan T, Zhou J, Lee J (2015) Who, what, when, and where: multi-dimensional collaborative recommendations using tensor factorization on sparse user-generated data. In Proceedings of the 24th International Conference on World Wide Web (WWW'15). International World Wide Web Conferences Steering Committee, Switzerland, p 130–140

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