Intelligent Recovery Architecture for Personalized Educational Content
Fecha de publicación
Springer Science + Business Media
Highlights on Practical Applications of Agents and Multi-Agent Systems Advances in Intelligent and Soft Computing. 10th International Conference on Practical Applications of Agents and Multi-Agent Systems. Advances in Intelligent and Soft Computing. Volumen 156, pp. 85-93.
Multi-agent systems are known for their ability to adapt quickly and effectively to changes in their environment. This work proposes a model for the development of digital content retrieval based on the paradigm of virtual organizations of agents. The model allows the development of an open and flexible architecture that supports the services necessary to conduct a search for distributed digital content dynamically. AIREH (Architecture for Intelligent Recovery of Educational content in Heterogeneous Environments) is based on the proposed model; it is a multi-agent architecture that can search and integrate heterogeneous educational content through a recovery model that uses a federated search. A major challenge in searching and retrieval digital content is to efficiently find the most suitable for the users This paper proposes a new approach to filter the educational content retrieved based on Case-Based Reasoning (CBR).The model and the technologies presented in this research are an example of the potential for developing recovery systems for digital content based on the paradigm of virtual organizations of agents. The advantages of the proposed architecture are its flexibility, customization, integrative solution and efficiency.
978-3-642-28761-9 (Print) / 978-3-642-28762-6 (Online)
1867-5662 (Print) / 1867-5670 (Online)
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