Fab: content-based, collaborative recommendation
Communications of the ACM
Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Getting to know you: learning new user preferences in recommender systems
Proceedings of the 7th international conference on Intelligent user interfaces
Methods and metrics for cold-start recommendations
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Exploring Versus Exploiting when Learning User Models for Text Recommendation
User Modeling and User-Adapted Interaction
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Building a Recommender Agent for e-Learning Systems
ICCE '02 Proceedings of the International Conference on Computers in Education
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
IEEE Transactions on Knowledge and Data Engineering
Koba4MS: Selling Complex Products and Services Using Knowledge-Based Recommender Technologies
CEC '05 Proceedings of the Seventh IEEE International Conference on E-Commerce Technology
Making recommendations better: an analytic model for human-recommender interaction
CHI '06 Extended Abstracts on Human Factors in Computing Systems
W4A '07 Proceedings of the 2007 international cross-disciplinary conference on Web accessibility (W4A)
Recommenders in a personalized, collaborative digital library environment
Journal of Intelligent Information Systems
International Journal of Learning Technology
Navigation support for learners in informal learning environments
Proceedings of the 2008 ACM conference on Recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
USAB '08 Proceedings of the 4th Symposium of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society on HCI and Usability for Education and Work
Recommending in Inclusive Lifelong Learning Scenarios: Identifying and Managing Runtime Situations
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Intelligent Support for Inclusive eLearning
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
ICWL '009 Proceedings of the 8th International Conference on Advances in Web Based Learning
Building a knowledge-based recommender for inclusive eLearning scenarios
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Guiding Learners in Learning Management Systems through Recommendations
EC-TEL '09 Proceedings of the 4th European Conference on Technology Enhanced Learning: Learning in the Synergy of Multiple Disciplines
ReMashed --- Recommendations for Mash-Up Personal Learning Environments
EC-TEL '09 Proceedings of the 4th European Conference on Technology Enhanced Learning: Learning in the Synergy of Multiple Disciplines
Educational data mining: a review of the state of the art
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Monitoring contributions online: a reputation system to model expertise in online communities
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Automatic discovery of complementary learning resources
EC-TEL'11 Proceedings of the 6th European conference on Technology enhanced learning: towards ubiquitous learning
Dataset-driven research for improving recommender systems for learning
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Recommendation in e-learning social networks
ICWL'11 Proceedings of the 10th international conference on Advances in Web-Based Learning
A hybrid user-centred recommendation strategy applied to repositories of learning objects
International Journal of Web Based Communities
Semi-automatic assembly of learning resources
Computers & Education
Evaluating collaborative filtering recommendations inside large learning object repositories
Information Processing and Management: an International Journal
Static and dynamic user portraits
Advances in Human-Computer Interaction - Special issue on User Assessment in Serious Games and Technology-Enhanced Learning
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This article argues that there is a need for Personal Recommender Systems (PRSs) in Learning Networks (LNs) in order to provide learners with advice on the suitable learning activities to follow. LNs target lifelong learners in any learning situation, at all educational levels and in all national contexts. They are community-driven because every member is able to contribute to the learning material. Existing Recommender Systems (RS) and recommendation techniques used for consumer products and other contexts are assessed on their suitability for providing navigational support in an LN. The similarities and differences are translated into specific requirements for learning and specific requirements for recommendation techniques. The article focuses on the use of memory-based recommendation techniques, which calculate recommendations based on the current data set. We propose a combination of memory-based recommendation techniques that appear suitable to realise personalised recommendation on learning activities in the context of e-learning. An initial model for the design of such systems in LNs and a roadmap for their further development are presented.