Automatic Learning Object Extraction and Classification in Heterogeneous Environments

摘要

This paper proposes the use of federated databases techniques in search-ing for educational resources by using a learning object paradigm that describes these resources based on metadata. Combining a complete agent-based architecture that implements the concept of federated search along with IR technologies may help organizing and sorting search results in a meaningful way for educational con-tent. The paper presents also the ground for an approach for semantic-aware learn-ing content retrieval based on abstraction layers between the repositories and the search clients.