A Multiagent Model for Searching Learning Objects in Heterogeneous Set of Repositories

Abstract

This paper proposes a multiagent system application model for indexing and retrieving 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 we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.

Personal Generative Library of Educational Resources: A Framework, Model and Implementation

“…al. [44] and study of J. Vian et al [45] proposes a multi-agent model for searching, recovering, recommendation and evaluation of LOs from Repository Federations. The study of S. Oton et al [46] highlights that "most repositories are usually autonomous, that is, they work as portals that can be accessed through a Web-based interface, providing a search mechanism and a list of categories to conduct the search", and offer the possibility of making federated searches in distributed repositories from the original repository.…”