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Título : A Fuzzy Cognitive Map like Recommender System of Learning Resources
Autor : Aguilar Castro, J.
Valdiviezo Diaz, P.
Riofrio Calderon, G.
Palabras clave : Fuzzy Cognitive Maps
Recommender Systems
Learning Resources.
metadata.dc.date.available: 2016-04-14
2017-06-16T22:02:17Z
Fecha de publicación : 7-nov-2016
Editorial : 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016
Resumen : In this paper we propose a Fuzzy Cognitive Maps (FCMs) to recommender Learning Resources in a Smart Classroom. We have proposed a Smart Environment for a Classroom in previous works, based on Multi-agent Systems, called SaCI. One of its agents is a recommender system of Learning Resources. In this paper, we define this recommender system using Fuzzy Cognitive Maps. Our recommender system exploits the knowledge, learns, discovers new information, infers preferences, among other thing. For that, it uses five types of knowledge from SaCI: students, learning resources, topics, context and criticism. The performance results of our recommender system based on FCMs are very encouraging.
metadata.dc.identifier.other: 10.1109/FUZZ-IEEE.2016.7737873
URI : http://dspace.utpl.edu.ec/handle/123456789/18741
Otros identificadores : 10.1109/FUZZ-IEEE.2016.7737873
Otros identificadores : 10.1109/FUZZ-IEEE.2016.7737873
metadata.dc.language: Inglés
metadata.dc.type: Article
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