Title: Learning object retrieval in heterogeneous environments

Authors: Ana B. Gil; Sara Rodríguez; Fernando De la Prieta; Juan Manuel Corchado

Addresses: Computer and Automation Department, University of Salamanca, Plaza de la Merced s/n, 37008, Salamanca, Spain ' Computer and Automation Department, University of Salamanca, Plaza de la Merced s/n, 37008, Salamanca, Spain ' Computer and Automation Department, University of Salamanca, Plaza de la Merced s/n, 37008, Salamanca, Spain ' Computer and Automation Department, University of Salamanca, Plaza de la Merced s/n, 37008, Salamanca, Spain

Abstract: This paper presents a solution to the problem of the search and retrieval digital tagged content in heterogeneous learning object repositories through architecture for intelligent retrieval of educational content in heterogeneous environments (AIREH) framework. This architecture unifies the search and retrieval of objects, thus facilitating the personalised learning search process by filtering and properly classifying learning objects retrieved for an approach for semantic-aware learning content retrieval based on abstraction layers between the repositories and the search clients. The use of federated databases techniques by using an organisation of agents allows those agents to work in a coordinated manner to solve a common problem, allowing the agents to adapt to the constantly changing environment (users, content repositories, etc.). Combining a complete agent-based architecture that implements the concept of federated search along with IR technologies may help organising and sorting search results in a meaningful way for educational content.

Keywords: multi-agent systems; MAS; distributed computing; e-learning; learning objects; repositories; simple query interface; SQI; learning technology standards; web services; object retrieval; agent-based systems; electronic learning; online learning; web search; information retrieval; digital tagged content; intelligent retrieval; educational content; personalised learning; semantic awareness; learning content retrieval.

DOI: 10.1504/IJWET.2013.055707

International Journal of Web Engineering and Technology, 2013 Vol.8 No.2, pp.197 - 213

Published online: 31 Mar 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article