2024-03-29T01:52:23Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1276252022-02-07T16:12:02Zcom_10366_127389com_10366_122682com_10366_4666com_10366_3823col_10366_127609
Multi-agent system for Knowledge-based recommendation of Learning Objects
Rodríguez Marín, Paula Andrea
Duque, Néstor
Ovalle, Demetrio
Computación
Informática
Computing
Information Technology
Learning Object (LO) is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS) can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.
2016-02-26T12:06:17Z
2016-02-26T12:06:17Z
2015-10-07
info:eu-repo/semantics/article
info:eu-repo/semantics/article
ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 4 (2015)
2255-2863
http://hdl.handle.net/10366/127625
eng
Attribution-NonCommercial-NoDerivs 3.0 Unported
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
application/pdf
Ediciones Universidad de Salamanca (España)