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Abstract
The rapid advances in Web technologies are promoting the development of new pedagogic models based on virtual teaching. To achieve this personalized services are necessary to provide the users with relevant information, according to their preferences and needs. Recommender systems can be used in an academic environment to improve and assist users in their teaching-learning processes. In this paper we propose a fuzzy linguistic recommender system to facilitate learners the access to e-learning resources interesting for them. By suggesting didactic resources according to the learner’s specific needs, a relevance-guided learning is encouraged, influencing directly the teaching-learning process. We propose the combination of the relevance degree of a resource for a user with its quality in order to generate more profitable and accurate recommendations. In addition to that, we present a computer-supported learning system to teach students the principles and concepts of recommender systems.
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References
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Acknowledgments
This paper has been developed with the financing of Projects UJA2013/08/41, TIN2013-40658-P, TIC5299, TIC-5991, TIN2012-36951 co-financed by FEDER and TIC6109.
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Authors and Affiliations
Departament of Computer Science, University of Jaén, Jaén, Spain
Carlos Porcel
Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
Maria Jesús Lizarte, Juan Bernabé-Moreno & Enrique Herrera-Viedma
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- Maria Jesús Lizarte
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- Enrique Herrera-Viedma
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Correspondence toCarlos Porcel.
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Editors and Affiliations
Wroclaw University of Technology, Wroclaw, Poland
Konrad Jackowski
Department of Systems, Wroclaw University of Technology, Wroclaw, Poland
Robert Burduk
Wroclaw Univ of Tech, Wroclaw, Poland
Krzysztof Walkowiak
Wroclaw University of Technology, Faculty of Electronics, Wroclaw, Poland
Michal Wozniak
School of Electrical & Electronic E, University of Manchester, Manchester, United Kingdom
Hujun Yin
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Porcel, C., Lizarte, M.J., Bernabé-Moreno, J., Herrera-Viedma, E. (2015). A Learning Web Platform Based on a Fuzzy Linguistic Recommender System to Help Students to Learn Recommendation Techniques. In: Jackowski, K., Burduk, R., Walkowiak, K., Wozniak, M., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2015. IDEAL 2015. Lecture Notes in Computer Science(), vol 9375. Springer, Cham. https://doi.org/10.1007/978-3-319-24834-9_57
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