# Smart System for the Retrieval of Digital Educational Content
## 3 Model of the AIREH Architecture  
### On the Proposed Solution  
It is necessary to search for new paradigms and applications which are going to optimize the search for educational content distributed in different formats, servers, and networks. This paper proposes an Architecture for Intelligent Retrieval of Educational content from Heterogeneous environments, called by its acronym AIREH, as a solution. AIREH is an architecture for federated search of educational contents, specifically the so-called LO. This federated search system consists of a series of elements: the repositories are distributed in physically dispersed places, access to these repositories is read-only, information systems operate under different platforms, repositories are distributed (metadata stored in one site and LO in another) and are managed by autonomous systems, in some cases access to repositories requires the creation of a session, in others the access is direct, etc. In this sense, the choice of a multi-agent system (MAS) architecture has been ideal for the development of a retrieval system. This is because the characteristics (autonomy, situation, reactivity, rationality, intelligence, organization, mobility and learning) [58] of agent architectures have ensured the development of a stable system, with the ability to react intelligently to the needs of the environment. The architecture has been modeled as a virtual organization, because an organization can adapt its actions to changes in the environment, achieving its objectives and interacting with heterogeneous components. As a result, the authors have considered it to be an effective solution. Education is a technologically heterogeneous and continually changing sector. The motivation behind this proposal is to enable teachers and students to optimally reuse educational content. To this end, it is necessary to establish effective processes for the search and retrieval of educational content. The article proposes a model with an agent-based virtual organization architecture, where the tasks associated with the federated search of educational content, are distributed among different agent organizations. The innovation of this proposal lies in the flexibility of the proposed system, a feature that derives from the underlying architecture. Moreover, the ability of agents to self-adapt to highly dynamic environments makes the model adaptable to changes. The AIREH architecture distributes the different tasks among nodes, as illustrated in Figure 1. As shown, the federated search for LOs involves six separate tasks. The first task (federated search and repository selection) is to initiate and supervise the entire federated search process. In addition, the active repositories that are relevant to the query are detected. The second task (classification, cataloging, etc.) involves the ranking and classification of the retrieved LOs. The next task is to store the LO processing results and statistics. After that, a filtering process is carried out to extract useful information, according to the search criteria established by the user. To provide the user with the most accurate solutions, we have coupled AIREH with a case-based reasoning system that learns from previous search experiences. The CBR system can adapt past solutions to new cases, facilitating the search process and increasing the accuracy of the results delivered to the user. Finally, as a result of completing the tasks described above, new features are applied in the search for an answer to the user's query. The proposed architecture solves the problems associated with repository distribution, integration, and internal logic. It also provides a solution for the classification, storage, and retrieval of LOs, in a completely transparent way. In addition, AIREH is a scalable architecture, which means that it is going to be compatible with new protocols, the architecture also includes internal components, such as repositories, catalogs or heterogeneous applications designed to cover service-related features.