Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Integrating structured data and text: a relational approach
Journal of the American Society for Information Science
GlOSS: text-source discovery over the Internet
ACM Transactions on Database Systems (TODS)
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Respecting the human needs of students in the development of e-learning
Computers & Education
A Taxonomy of Recommender Agents on theInternet
Artificial Intelligence Review
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Building a Recommender Agent for e-Learning Systems
ICCE '02 Proceedings of the International Conference on Computers in Education
Swarm-based Sequencing Recommendations in E-learning
ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
Supporting Pervasive Learning Environments: Adaptability and Context Awareness in Mobile Learning
WMTE '05 Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education
Distributed collaborative filtering with domain specialization
Proceedings of the 2007 ACM conference on Recommender systems
Content-based recommendation systems
The adaptive web
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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Educational standards that include content metadata description for materials have great potential for managing e-learning information and content units and facilitate their interoperability and reutilisation. These open semantic and distance learning aspects contribute new and important possibilities for online education systems. The Learning Objects (LOs) paradigm focuses this new gap on the management and exchange of educational materials. This paper presents an application approach to educational content recommendation based on Learning Objects. It describes an architecture based on a multi-agent system with a bio-inspired algorithm rooted in self-organisation theory. It supports the retrieval, search, selection and composition of these LOs.