Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
The 3A contextual ranking system: simultaneously recommending actors, assets, and group activities
Proceedings of the third ACM conference on Recommender systems
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In the field of personal learning environment (PLE) research is focusing on the generation and provision of recommendations. Amongst others, approaches reach from decision making tools based on psycho-pedagogical principles over specialized social recommender functionality up to general community or context-aware recommendations. The variety of the solutions results from the fact that pure collaborative filtering (CF) techniques are not sufficient for PLE-based scenarios. In this paper we propose utilizing learner interaction recordings for generating PLE recommendations fitting the educational and social context of a learner. Besides pointing out how we have realized this approach as part of a research prototype, we evaluate and discuss such recommendations generated from data captured in former studies.