Model of Recommendation System for for Indexing and Retrieving the Learning Object based on Multiagent System
Modelo de sistema de recomendación para la indexación y recuperación del objeto de aprendizaje basado en un sistema multiagente
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This paper proposes a multiagent system application model for indexing, retrieving and recommendation learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata 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 signification of the results we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.
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