Skip to Main Content
In the current educational context there has been a significant increase in learning object repositories (LOR), which are found in large databases available on the hidden web. All the information about these learning objects (LOs) is described in any metadata labeling standard (LOM, Dublin Core, etc). It is necessary to work and develop solutions that provide efficiency in searching for heterogeneous content and finding distributed context. Distributed information retrieval, or federated search, attempts to respond to the problem of information retrieval in the hidden Web. The main aim of a federated search is to develop models and strategies to get the most benefit from these distributed sources. Thus, users perceive the system as a single point of access to information they require, regardless of the number of sources that exist, its location, or its management mechanism. The process is completely transparent to the user, who does not perceive its complexity and therefore treats any of the information retrieved uniformly. This paper describes an architecture that recovers educational content, called AIREH (Architecture for Intelligent Recovery of Educational content in Heterogeneous Environments), which combines the dynamism and flexibility of multi-agent organizations. The proposal uses systems and mechanisms by which agents acquire roles based on the generation and use of dynamic web services.