Please use this identifier to cite or link to this item: http://dspace.utpl.edu.ec/handle/123456789/18741
Title: A Fuzzy Cognitive Map like Recommender System of Learning Resources
Authors: Aguilar Castro, J.
Valdiviezo Diaz, P.
Riofrio Calderon, G.
Keywords: Fuzzy Cognitive Maps
Recommender Systems
Learning Resources.
Issue Date: 7-Nov-2016
Publisher: 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016
Abstract: 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.
URI: http://dspace.utpl.edu.ec/handle/123456789/18741
Other Identifiers: 10.1109/FUZZ-IEEE.2016.7737873
Appears in Collections:Artículos de revistas Científicas

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