2024-03-29T08:54:42Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1305292022-02-07T16:12:08Zcom_10366_127389com_10366_122682com_10366_4666com_10366_3823col_10366_130521
00925njm 22002777a 4500
dc
Silveira, Ricardo Azambuja
author
Comarella, Rafaela Lunardi
author
Campos, Ronaldo Lima Rocha
author
Vian, Jonas
author
Prieta Pintado, Fernando de la
author
2015-12-24
This paper discusses some important issues regarding the the management of Learning objects covering searching over repositories and different approaches of recommendation systems and presents a multiagent system based application model for indexing, retrieving and recommending learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata (data about data) standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the relevance of the results we propose an information retrieval model based on a multiagent system approach and an ontological model to describe the covered knowledge domain.
ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 4 (2015)
2255-2863
http://hdl.handle.net/10366/130529
Computación
Informática
Computing
Information Technology
Learning Objects Recommendation System: Issues and Approaches for Retrieving, Indexing and Recomend Learning Objects